Attachment 1 - Draft PWS.docx
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- Solicitation number
- 5000233302
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This is a Draft Performance Work Statement (PWS) for Enterprise Data Pipeline Modernization and Data Consumption Services issued by the Internal Revenue Service. The requirement encompasses design, development, modernization, testing, deployment, and operational support of enterprise data pipelines within the Enterprise Data Platform, with primary focus on Databricks pipeline development, data ingestion, transformation, business intelligence consumption, self-service analytics, natural-language query capabilities, AI-assisted legacy modernization, and production operations support. The contractor must support data pipeline teams responsible for acquiring data from legacy and modern source systems (including IBM mainframe, Unisys OS 2200, COBOL for z/OS, and DB2), transforming and curating data in Databricks and AWS services, and publishing trusted data products for consumption by Tableau, Business Objects Enterprise, Power BI, APIs, and self-service analytics tools.
The PWS defines twelve major task areas: Transition-In (one month), Program Intake and Platform Migration Port/Test, Source System Analysis and Data Acquisition, Databricks Pipeline Development and Transformation, Data Product Design and BI Consumption, Metadata/Governance/Security/Data Quality, Self-Service Analytics and Natural-Language Query Enablement, AI-Assisted Legacy Modernization Support, DevSecOps/Automation/Deployment, Testing/Performance/Production Readiness, Operations/Maintenance/Production Support, and Transition-Out (one month). The period of performance consists of a one-month Transition-In period, one 12-month base period, two 12-month option periods, and a one-month Transition-Out period (March 1, 2027 through February 28, 2030). Primary place of performance is the contractor's facility, with possible work required at IRS locations in Lanham Maryland, Memphis Tennessee, Austin Texas, Dallas Texas, and Ogden Utah. The government will furnish property including contractor identification badges, laptop computers with network access, office space if requested, and information including manuals and directives. Key personnel positions are designated for Data Pipeline Technical Lead, Senior Databricks Data Engineers, Legacy Data Modernization/Mainframe Integration Lead, Data Governance/Metadata/Data Quality Lead, DevSecOps/Deployment Automation Lead, BI and Semantic Layer Lead, AI/Natural-Language Query Enablement Lead, and Production Support/Site Reliability Lead, with strict controls on substitution prohibiting voluntary changes during the first 180 calendar days after award. The contractor must submit commitment letters and availability certifications for all proposed key personnel before award, and substitution requests require minimum 30 calendar days advance notice with detailed qualification comparisons and transition plans.
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Draft PWS - Enterprise Data Pipeline Modernization and Data Consumption Services Draft Performance Work Statement (PWS) Enterprise Data Pipeline Modernization and Data Consumption Services Databricks Pipeline Development, BI Consumption, Self-Service Analytics, Natural-Language Query, AI-Assisted Legacy Modernization, and Limited Platform Port/Test Support
Table of Contents
| 1. Purpose | 4 |
| 2. Background | 4 |
| 3. Objectives | 4 |
| 4. Technical Environment | 4 |
| 4.1 Cloud and Data Platform Services | 5 |
| 4.2 Data Integration and Movement | 5 |
| 4.3 Business Intelligence and Consumption | 5 |
| 4.4 Legacy and Mainframe Sources | 5 |
| 4.5 Governance, Metadata, and DevSecOps | 5 |
| 5. Scope of Work | 5 |
| 5.1 Task Area (1): Transition In (Ramp-Up Knowledge Transfer) | 6 |
| 5.2 TASK AREA (2): Program Intake, Backlog Planning, and Platform Migration Port/Test Tasks | 7 |
| 5.3 TASK AREA (3): Source System Analysis and Data Acquisition | 7 |
| 5.4 TASK AREA (4): Databricks Pipeline Development and Transformation | 7 |
| 5.5 TASK AREA (5): Data Product Design and BI Consumption | 8 |
| 5.6 TASK AREA (6): Metadata, Governance, Security, and Data Quality | 8 |
| 5.7 TASK AREA (7): Self-Service Analytics and Natural-Language Query Enablement | 8 |
| 5.8 TASK AREA (8): AI-Assisted Legacy Modernization Support | 9 |
| 5.9 TASK AREA (9): DevSecOps, Automation, and Deployment | 9 |
| 5.10 TASK AREA (10): Testing, Performance, and Production Readiness | 9 |
| 5.11 TASK AREA (11): Operations, Maintenance, and Production Support | 10 |
| 5.12 TASK AREA (12): Transition-Out (Knowledge Transfer) | 10 |
| 6. Deliverables | 11 |
| 7. Performance Standards | 12 |
| 8. Coordination Requirements | 13 |
| 9. Assumptions and Dependencies | 13 |
| 10. Government Responsibilities | 13 |
| 11. Contractor Responsibilities | 14 |
| 12. Key Personnel, Staffing Continuity, and Substitution Controls | 14 |
| 12.1 Key Personnel Positions | 14 |
| 12.2 Government Furnished Property (GFP) and Government Furnished Information (GFI) | 14 |
| 12.3 Materiality of Key Personnel | 15 |
| 12.4 Key Personnel Commitment Letters and Availability Certification | 15 |
| 12.5 Restriction on Substitution, Reassignment, and Reduced Level of Effort | 15 |
| 12.6 Notice of Actual or Anticipated Unavailability | 15 |
| 12.7 Required Substitution Request Package | 16 |
| 12.8 Approval Standard for Replacement Personnel | 16 |
| 12.9 Transition Overlap and Knowledge Transfer | 16 |
| 12.10 Temporary Absence and Interim Backfill | 16 |
| 12.11 Government-Directed Removal | 16 |
| 12.12 Unauthorized Substitution and Remedies | 17 |
| 12.13 Applicability to Subcontractors, Consultants, and Team Members | 17 |
| 12.14 Incorporation into Contract Baseline | 17 |
| 12.15 PERIOD OF PERFORMANCE | 17 |
| 12.15 PLACE OF PERFORMANCE | 17 |
| 12.16 TRAVEL | 17 |
| 13. Acronyms | 17 |
| 14. Performance Requirements Summary (PRS) | 18 |
1. Purpose The purpose of this Performance Work Statement is to obtain contractor support for the design, development, modernization, testing, deployment, and operational support of enterprise data pipelines within the Enterprise Data Platform. The work is primarily focused on Databricks pipeline development, data ingestion, transformation, BI consumption, self-service analytics, natural-language query, AI-assisted legacy modernization, and sustainable production operations. Platform migration activities, including EDP or CSB environment transition work when assigned, are limited to porting, configuration updates, execution testing, validation, and defect remediation unless the Government separately approves redesign or modernization.
The contractor shall support a data pipeline team responsible for acquiring data from legacy and modern source systems, transforming and curating data in Databricks and related AWS services, and publishing trusted data products for consumption by Tableau, Business Objects Enterprise, Power BI, APIs, self-service analytics, natural-language query capabilities, and AI-enabled modernization use cases.
2. Background The Enterprise Data Platform supports mission-critical data integration, analytics, reporting, and application use cases across multiple business verticals and enterprise programs. The current environment includes AWS cloud services, Databricks, relational and NoSQL databases, legacy mainframe data sources, enterprise BI tools, metadata and governance tools, and DevSecOps automation.
The platform must continue to support existing production workloads while modernizing ingestion, transformation, governance, metadata, and consumption patterns. Key business and technical drivers include:
Limited platform migration support for assigned pipelines, consisting of porting, configuration updates, dependency validation, execution testing, and defect remediation as target platform environments change.
Modernization of ingestion from legacy IBM, Unisys OS 2200, COBOL for z/OS, DB2, and related mainframe sources.
Development of Databricks-based ETL and ELT pipelines.
Delivery of curated data products for Tableau, Business Objects Enterprise, and Power BI.
Support for Compliance Hub, Document Matching, TSOA/IOLA migration, Trump Accounts, Clean Energy, and other priority verticals or applications.
Enablement of self-service analytics, governed data discovery, semantic layers, natural-language query, and AI-assisted modernization of legacy programs.
3. Objectives
| 1. | Modernize data ingestion and transformation by designing and implementing secure, repeatable, automated Databricks pipelines that acquire data from legacy and modern source systems. |
| 2. | Provide trusted data products for consumption by creating curated, governed, documented, and performance-optimized datasets for Tableau, Business Objects Enterprise, Power BI, APIs, and other approved consumers. |
| 3. | Improve data governance and discoverability by integrating metadata, lineage, business definitions, ownership, security classifications, and access controls into enterprise metadata and governance tools. |
| 4. | Enable self-service and natural-language analytics by preparing governed semantic layers, curated datasets, business-friendly metadata, data access workflows, and AI-ready data products. |
| 5. | Support AI-assisted legacy modernization by analyzing legacy programs, copybooks, data structures, job schedules, dependencies, business rules, and transformation logic to support modernization planning and implementation. |
| 6. | Provide sustainable operations by implementing monitoring, alerting, restartability, runbooks, deployment automation, testing, data-quality checks, and production support processes. |
4. Technical Environment The contractor shall support work across the following technologies, services, and integration patterns, as applicable to approved Government requirements.
4.1 Cloud and Data Platform Services
AWS.
Databricks.
AWS RDS PostgreSQL.
AWS Redshift.
AWS DynamoDB.
AWS Aurora, where directed or under evaluation.
AWS DMS.
AWS DataSync.
Supporting AWS services for storage, networking, monitoring, security, identity, logging, and automation.
4.2 Data Integration and Movement
On-premises Informatica.
EFTU or enterprise file-transfer mechanisms.
Databricks ETL and ELT.
AWS DMS.
AWS DataSync.
Kafka or event-driven data movement, where applicable.
Batch, incremental, CDC, streaming, and file-based ingestion patterns.
4.3 Business Intelligence and Consumption
Business Objects Enterprise.
Tableau.
IRS Power BI.
APIs and application feeds.
Self-service query tools.
Natural-language query capabilities.
AI-enabled analytical and modernization use cases.
4.4 Legacy and Mainframe Sources
IBM mainframe sources.
Unisys OS 2200 sources.
COBOL for z/OS programs.
DB2.
Copybooks.
JCL or equivalent job schedules.
Flat files, extracts, and legacy data movement patterns.
Business rules embedded in legacy programs or transformation logic.
4.5 Governance, Metadata, and DevSecOps
Informatica Enterprise Data Catalog.
Informatica Axon.
Immuta.
Jira.
Confluence.
GitHub.
GitHub Actions or comparable automation tools.
Databricks Asset Bundles.
Enterprise security, logging, monitoring, and configuration-management services.
5. Scope of Work The contractor shall provide enterprise data pipeline modernization and data consumption services. The contractor shall design, develop, test, deploy, and operate Databricks-based ingestion and transformation pipelines that acquire data from legacy and modern source systems, including mainframe, DB2, COBOL, file-based, database, Kafka, Informatica, and AWS-based sources. Platform migration support, including EDP or CSB transition-related work when assigned, is limited to porting existing pipelines, updating configurations and dependencies, executing validation tests, remediating defects, and confirming consumer readiness. The contractor shall transform and curate data into governed, documented, quality-checked data products for Tableau, Business Objects Enterprise, Power BI, APIs, self-service analytics, natural-language query, and AI-enabled modernization use cases. The contractor shall also support metadata, lineage, data quality, access controls, DevSecOps automation, performance optimization, production readiness, operational runbooks, incident response, key-personnel continuity, and knowledge transfer to Government personnel.
The Contractor shall perform the following twelve (12) major task areas. The formal deliverables supporting these task areas are identified in Section 6, Deliverables.
5.1 Task Area (1): Transition In (Ramp-Up Knowledge Transfer) The Transition-In period shall not exceed one (1) month. During this period, the Contractor shall, upon the Contracting Officer's written notice, furnish Transition-In services as required. As the successor contractor, the Contractor shall have sufficient personnel in place throughout the Transition-In period to ensure a smooth transition from the incumbent Contractor. The Contractor shall provide an orderly transition of work responsibilities to minimize any disruption to Government operations. During the Transition-In period, the Contractor shall become familiar with the requirements, systems, processes, and operational environment to ensure full performance of all contract requirements upon completion of the transition. Transition-In services are not required if the successor contractor is the incumbent Contractor.
The Contractor will appoint a knowledge transfer manager to oversee the transfer of knowledge and ensure all areas are accounted for. If desired, this can be the Project Manager or Project Scheduler. Prior to the transfer of knowledge, the Contractor must develop a draft Knowledge Transfer Plan (KTP) and present it to the Government within the first 10 business days after award. The KTP must identify the Contractor resources and roles involved in the transfer process, provide a list of risks and mitigation strategies for the transfer, and contain a detailed resource balanced project schedule developed with Microsoft Project. The project schedule will identify tasks, dependencies, deliverables, and milestones. The project schedule must be at a sufficient level of detail to track progress on a bi-weekly basis (that is, all tasks will be detailed to a level such that no task has duration of more than 10 workdays). The Government will have five business days to review the draft KTP and provide comments to the Contractor. Government and Contractor representatives will then meet to discuss the comments after which the Contractor must incorporate the agreed-upon changes and deliver a final KTP within five working days of the Government’s feedback. The Contractor will meet with the IRS weekly to discuss the progress of the knowledge transfer. The Contractor must show an updated MS Project Schedule and discuss any risks or concerns at this time. The Contractor must also develop a Transition-In Checklist 10 business days after award to provide a vehicle to verify completion of the necessary transition-in activities. Transition-In checklist must ensure fulfillment of all applicable contractor on-boarding requirements within Appendix E. The Transition-In Checklist must be signed by both the Contractor and the Contracting Officer’s Representative (COR) after completion of the task. The Contractor will perform the following activities during the transition-in period:
a) Assign personnel and submit security papers promptly to get the background investigations done quickly and gain access to IRS’s network
b) Request access to tools and documentation
c) Review and understand all the technical and process documentation
d) Review and understand the existing data and product security policies in place
e) The contractor must provide Ramp-Up Staffing Plan and describe how they will bring resources on board in coordination with the ramp-down efforts of the incumbent
f) The contractors must provide Knowledge Transfer Plan/Checklist Ramp-Up Knowledge Transfer is defined as the Contractor acquiring and understanding the necessary documentation, information, and processes related to any work in progress. This task includes meeting with the IRS Subject Matter Experts and incumbent personnel frequently to gather any tacit knowledge related to the core required tasks.
Transition-In must be worked concurrently with Ramp-Up Knowledge Transfer. Successful transition can be defined by its capacity to maintain full continuity of operations, high productivity, and exemplary service quality. During the transition-in period, the incumbent is responsible for performance. The government estimates these tasks will take approximately one to two months to complete after award.
5.2 TASK AREA (2): Program Intake, Backlog Planning, and Platform Migration Port/Test Tasks Platform migration tasks under this PWS are limited to porting and testing assigned pipelines, jobs, configurations, dependencies, and data products when target platform environments change. This includes tasks required for EDP 1.0 to EDP 2.0 or CSB 1.0 to CSB 2.0 environment moves when directed by the Government, but does not create a separate modernization, redesign, or application-rewrite workstream unless separately authorized. The contractor shall:
| 1. | Inventory assigned pipelines, jobs, APIs, databases, source feeds, target datasets, schedules, dependencies, consumers, owners, and operational support procedures. |
| 2. | Assess each assigned pipeline, job, API, or data product for technical readiness, source-system dependency, business criticality, security classification, data sensitivity, performance requirement, consumer impact, and target-environment porting changes. |
| 3. | Port assigned pipelines, workflow definitions, job configurations, environment parameters, connection references, secrets references, libraries, deployment bundles, and permissions to the approved target platform environment when directed. |
| 4. | Validate ported pipelines through execution testing, data-quality checks, reconciliation, performance verification, security and access validation, BI or API consumer testing, and defect remediation. |
| 5. | Coordinate with verticals and application teams, including Compliance Hub, Document Matching, TSOA/IOLA, Trump Accounts, Clean Energy, and other approved stakeholders. |
| 6. | Identify dependencies on source-system teams, platform teams, security teams, BI teams, metadata teams, API teams, and application consumers. |
| 7. | Maintain and track a prioritized pipeline modernization and platform port/test backlog in Jira or another Government-approved work-management tool, including port/test readiness, development progress, testing status, deployment status, production issues, and post-deployment stabilization metrics. |
5.3 TASK AREA (3): Source System Analysis and Data Acquisition The contractor shall:
| 1. | Analyze source data structures, schemas, copybooks, DB2 tables, files, extracts, Kafka topics, Informatica mappings, database replication patterns, and business rules. |
| 2. | Document source-to-target mappings, transformation rules, data-quality rules, reconciliation rules, data sensitivity, refresh frequency, expected volume, and latency requirements. |
| 3. | Design ingestion patterns for batch, incremental, CDC, file-based, database-based, API-based, or event-driven data acquisition. |
| 4. | Build ingestion pipelines from approved legacy and modern sources into the EDP environment. |
| 5. | Implement controls for file arrival, schema validation, duplicate detection, reconciliation, error handling, restartability, audit logging, and lineage tracking. |
| 6. | Validate that ingested data matches approved source counts, control totals, record layouts, business rules, and reconciliation thresholds. |
| 7. | Coordinate with source-system owners to resolve data availability, extract timing, schema changes, connectivity, access, and data-quality issues. |
5.4 TASK AREA (4): Databricks Pipeline Development and Transformation The contractor shall:
| 1. | Develop ETL and ELT pipelines using approved Databricks patterns, Spark, SQL, Python, Delta Lake, workflows, notebooks, jobs, and Databricks Asset Bundles. |
| 2. | Implement medallion or equivalent data-layering patterns, including raw, standardized, curated, and consumption-ready data layers. |
| 3. | Transform legacy source data into governed, documented, quality-checked, and consumption-ready data products. |
| 4. | Implement reusable pipeline components for ingestion, validation, transformation, logging, error handling, notification, metadata capture, and data-quality reporting. |
| 5. | Apply standard naming conventions, code standards, repository structures, branching practices, and deployment automation approved by the Government. |
| 6. | Implement parameterized and reusable code patterns to reduce duplication across similar source feeds, data products, and consumer outputs. |
| 7. | Optimize pipeline performance using appropriate partitioning, clustering, file sizing, caching, query optimization, incremental processing, workload sizing, and cost-control techniques. |
| 8. | Implement unit testing, integration testing, regression testing, data reconciliation, performance testing, and production-readiness testing. |
| 9. | Remediate defects identified during development, testing, production deployment, and post-deployment stabilization. |
5.5 TASK AREA (5): Data Product Design and BI Consumption
The contractor shall:
| 1. | Design curated tables, views, semantic structures, and consumption layers that support Tableau, Business Objects Enterprise, Power BI, APIs, and approved self-service tools. |
| 2. | Define data products with clear business purpose, source lineage, refresh frequency, data owner, steward, security classification, access requirements, and consumer groups. |
| 3. | Create BI-ready structures that minimize duplicated logic across Tableau, Business Objects Enterprise, and Power BI. |
| 4. | Coordinate with BI teams to validate that published data products support approved reports, dashboards, extracts, semantic models, universes, datasets, and ad hoc analysis. |
| 5. | Support performance tuning for BI workloads, including query optimization, SQL warehouse configuration, table design, materialized views, aggregate tables, and workload separation where approved. |
| 6. | Provide data access patterns that support both scheduled reporting and ad hoc analytical workloads. |
| 7. | Support API and application teams by publishing approved data products, extracts, feeds, or service-ready datasets. |
5.6 TASK AREA (6): Metadata, Governance, Security, and Data Quality The contractor shall:
| 1. | Capture and maintain technical metadata, business metadata, lineage, data ownership, data stewardship, definitions, source mappings, and transformation logic. |
| 2. | Integrate approved metadata into Informatica EDC, Axon, Databricks Unity Catalog, Immuta, or other Government-approved governance tools. |
| 3. | Apply approved access controls, including role-based, attribute-based, row-level, column-level, masking, tagging, entitlement, and policy-based controls where required. |
| 4. | Classify data according to Government-approved data sensitivity, privacy, records, disclosure, and security requirements. |
| 5. | Implement data-quality checks for completeness, validity, accuracy, consistency, uniqueness, timeliness, referential integrity, and business-rule compliance. |
| 6. | Produce data-quality metrics and exception reports for Government review. |
| 7. | Support data access review, entitlement validation, metadata completeness review, and remediation of governance findings. |
| 8. | Ensure pipelines comply with approved logging, auditing, encryption, network, identity, and access-management requirements. |
5.7 TASK AREA (7): Self-Service Analytics and Natural-Language Query Enablement The contractor shall:
| 1. | Prepare curated datasets for self-service use by ensuring data products have business-friendly names, descriptions, definitions, certified fields, lineage, ownership, and access instructions. |
| 2. | Create or support semantic models, business glossaries, data catalogs, and governed query patterns that allow users to discover and use approved data products. |
| 3. | Configure or support natural-language query capabilities using Government-approved tools, including Databricks Genie or comparable capabilities where authorized. |
| 4. | Validate natural-language query outputs against approved business definitions, SQL logic, row counts, filters, aggregations, and security rules. |
| 5. | Implement guardrails to reduce incorrect, unauthorized, or misleading query results. |
| 6. | Support onboarding materials, office hours, user guides, sample queries, and adoption support for business users and technical consumers. |
5.8 TASK AREA (8): AI-Assisted Legacy Modernization Support
The contractor shall:
| 1. | Analyze approved legacy artifacts, including COBOL programs, copybooks, JCL, DB2 schemas, file layouts, extracts, job schedules, and transformation logic. |
| 2. | Identify source data elements, business rules, dependencies, upstream and downstream systems, data lineage, batch sequencing, and modernization candidates. |
| 3. | Use approved AI, machine learning, or natural-language processing capabilities to assist with documentation, mapping, code understanding, data lineage, rule extraction, test-case generation, and modernization planning. |
| 4. | Validate AI-assisted outputs through human review, source-system comparison, business-owner review, and technical verification. |
| 5. | Produce modernization recommendations for Government approval, including candidate pipelines, reusable patterns, risk areas, testing requirements, and expected consumer impacts. |
| 6. | Support modernization of legacy extracts and transformation logic into Databricks-based pipelines where approved. |
5.9 TASK AREA (9): DevSecOps, Automation, and Deployment
The contractor shall:
| 1. | Maintain source code, configuration, tests, documentation, and deployment artifacts in Government-approved repositories. |
| 2. | Implement CI/CD pipelines using GitHub Actions, Databricks Asset Bundles, Terraform, or comparable Government-approved tools. |
| 3. | Automate deployment of Databricks jobs, notebooks, workflows, clusters, SQL warehouses, configuration, permissions, and pipeline artifacts where approved. |
| 4. | Implement environment promotion patterns for development, test, staging, and production. |
| 5. | Support change-management processes, release notes, deployment evidence, rollback plans, and production deployment coordination. |
| 6. | Validate that deployed artifacts match approved baselines, configuration standards, access policies, and operational requirements. |
| 7. | Maintain deployment traceability from requirement to code, test evidence, release package, and production deployment. |
5.10 TASK AREA (10): Testing, Performance, and Production Readiness The contractor shall:
| 1. | Develop test plans and test cases for ingestion, transformation, reconciliation, data quality, security, performance, failure recovery, restartability, and consumer validation. |
| 2. | Execute unit, system, integration, regression, performance, and user-acceptance support testing. |
| 3. | Validate source-to-target accuracy using record counts, control totals, sampling, business rules, reconciliation reports, and approved tolerance thresholds. |
| 4. | Conduct performance testing for scheduled jobs, BI queries, data refreshes, API feeds, self-service queries, and natural-language query use cases. |
| 5. | Document test results, defects, remediation actions, retesting results, and production-readiness status. |
| 6. | Support production deployments, post-deployment validation, warranty-period monitoring, and issue resolution. |
5.11 TASK AREA (11): Operations, Maintenance, and Production Support The contractor shall:
| 1. | Monitor scheduled pipeline execution, job status, data arrival, SLA compliance, data-quality exceptions, compute usage, and consumer-facing failures. |
| 2. | Triage and resolve incidents, failed jobs, data-quality issues, source-system delays, access issues, performance degradation, and consumer-reported defects. |
| 3. | Maintain runbooks, support procedures, escalation paths, operational dashboards, known-error logs, and production support documentation. |
| 4. | Support root-cause analysis and corrective actions for production incidents. |
| 5. | Implement improvements that reduce recurring failures, manual intervention, processing time, compute cost, and support burden. |
| 6. | Provide knowledge transfer to Government employees through documentation, paired execution, reverse shadowing, office hours, and formal walkthroughs. |
5.12 TASK AREA (12): Transition-Out (Knowledge Transfer)
The Transition-Out period shall consist of one (1) month. To minimize any decrease in productivity and to prevent possible negative impacts on additional services, the Contractor shall have sufficient personnel on board during the 1-month Transition-Out period. The Contractor shall ensure a smooth transition with the Government during the Transition-Out period, prior to completion of contractual performance. The Contractor shall aid the Government in the development of plans, procedures, and processes for the assumption of all on going work. The Contractor shall provide an orderly transition of work acceptance and accomplishment, such that full control by the Government is achieved by the end of the Transition Out period. The Transition Out CLIN may be exercised at any point during the duration of the contract.
The Contractor will provide a Transition-Out Plan six (6) months before the end of the contract. The Contractor shall be responsible for the transition of all technical activities identified in this PWS. As part of the transition, the Contractor will be responsible for:
a) Inventory and orderly transfer of all Government-Furnished Property (GFP), to include hardware, software, and licenses; Contractor Acquired Government Property; and Government Furnished Information (GFI).
b) Transfer of documentation currently in process.
c) Transfer of all software code in process.
d) Certification that all non-public IRS information has been purged from any Contractor-owned system.
e) Participate in knowledge transfer activities in accordance with the transition plan.
f) Provide personnel to and participate in transition management team.
g) If the Government provides a Transition-Out Plan template, the Contractor must complete it as assigned; otherwise, the Contractor must submit a Transition-Out Plan at the direction of the government
The Transition-Out Plan must:
a) Document the strategic approach.
b) Identify equipment, hardware, software, documents, and other artifacts that are included in the transition.
c) Document milestones and schedules.
d) Document work-in progress.
e) Identify transition risks and risk mitigation.
f) Define roles and responsibilities.
g) Define transition approval authorities and lines of communication.
6. Deliverables All deliverables shall be submitted in Government-approved formats and repositories, including Jira, Confluence, GitHub, Databricks, metadata tools, shared document repositories, or other approved systems. The contractor shall update deliverables as requirements change, defects are identified, or production changes occur.
| No. |
| Deliverable |
| Description and Acceptance Criteria |
| Frequency / Timing |
| 1 |
| Pipeline and Data Product Inventory |
| Inventory of existing and target-state pipelines, jobs, APIs, databases, source feeds, target datasets, consumers, schedules, owners, dependencies, and support procedures. Acceptance: includes all Government-assigned in-scope pipelines and data products; identifies source, target, owner, consumer, schedule, dependency, status, and port/test disposition where applicable. |
| Initial baseline; updated at least biweekly or as directed. |
| 2 |
| Platform Migration Porting and Test Plan |
| Plan for porting and validating assigned pipelines affected by approved platform environment changes, including EDP or CSB transition activities when directed. Acceptance: identifies impacted pipelines, configuration changes, target environment, dependency updates, test approach, consumer validation, defects, and readiness status; does not treat platform migration as a separate modernization workstream unless approved by the Government. |
| As assigned; updated with each port/test wave or as scope changes. |
| 3 |
| Requirements and Intake Package |
| Documented business, technical, security, metadata, data-quality, performance, and consumption requirements. Acceptance: includes source systems, target consumers, refresh frequency, volume, SLA, security classification, access needs, and acceptance criteria. |
| For each approved pipeline, data product, or platform port/test task. |
| 4 |
| Source-to-Target Mapping |
| Mapping of source fields, target fields, transformation rules, business rules, data types, default values, filters, joins, and reconciliation rules. Acceptance: approved by the Government or designated data owner; includes transformation logic and traceability to source artifacts. |
| For each pipeline or data product. |
| 5 |
| Technical Design Document |
| Pipeline and data product design, including architecture, ingestion pattern, transformation approach, data layers, security, metadata, testing, deployment, and operations. Acceptance: design is complete enough to support development, review, testing, deployment, and operations. |
| Before development completion or as directed. |
| 6 |
| Databricks Pipeline Code Package |
| Version-controlled code for notebooks, workflows, jobs, SQL, Python, Spark, Delta tables, configuration, and reusable components. Acceptance: code follows approved standards and includes logging, error handling, restartability, parameterization, and repository traceability. |
| For each approved pipeline release. |
| 7 |
| CI/CD and Deployment Package |
| Automated deployment artifacts using GitHub Actions, Databricks Asset Bundles, Terraform, or approved equivalent. Acceptance: includes deployment scripts, configuration, environment parameters, release notes, rollback steps, and deployment evidence. |
| For each release. |
| 8 |
| Data Quality and Reconciliation Package |
| Data-quality rules, validation results, reconciliation reports, exception handling, and remediation status. Acceptance: includes source-to-target counts, control totals, rule results, exceptions, and evidence that thresholds were met or approved exceptions were documented. |
| For each test cycle and production release. |
| 9 |
| Curated Data Product Package |
| Published tables, views, semantic structures, extracts, or feeds prepared for BI, API, application, self-service, or AI consumption. Acceptance: includes ownership, lineage, definitions, refresh frequency, access controls, and consumer validation evidence. |
| For each data product release. |
| 10 |
| BI Consumption Readiness Package |
| Evidence that data products support Tableau, Business Objects Enterprise, Power BI, or other approved consumers. Acceptance: includes validated queries, data model alignment, report/dashboard support, performance results, and consumer sign-off or documented approval. |
| For each BI-facing data product. |
| 11 |
| Metadata and Lineage Package |
| Metadata entries, lineage, ownership, stewardship, business definitions, data classification, and governance attributes. Acceptance: metadata is entered or updated in approved tools such as EDC, Axon, Unity Catalog, Immuta, or other approved repositories. |
| For each production data product and each major release. |
| 12 |
| Security and Access Control Package |
| Documentation and evidence of access controls, entitlements, masking, row-level security, column-level security, tags, and approval workflows. Acceptance: access controls align with approved requirements and are validated before production deployment. |
| For each production release and access-control change. |
| 13 |
| Self-Service and Natural-Language Query Readiness Package |
| Business-friendly descriptions, semantic structures, sample prompts, sample queries, validation results, and guardrails for self-service or natural-language query. Acceptance: outputs are validated against approved SQL logic, business definitions, security rules, and sample test cases. |
| For each approved self-service or natural-language query use case. |
| 14 |
| AI-Assisted Legacy Modernization Analysis |
| Analysis of legacy code, copybooks, job schedules, business rules, data lineage, and modernization candidates. Acceptance: includes reviewed AI-assisted findings, human validation notes, risk areas, source artifacts, recommended modernization approach, and candidate pipeline mappings. |
| For each approved legacy modernization effort. |
| 15 |
| Test Plan and Test Results |
| Test cases and results for unit, integration, regression, performance, security, data quality, reconciliation, and user-acceptance support testing. Acceptance: includes pass/fail status, defects, remediation, retesting evidence, and unresolved risk or exceptions. |
| For each release or test cycle. |
| 16 |
| Performance and Optimization Report |
| Analysis of pipeline run time, query performance, compute usage, cost drivers, bottlenecks, and optimization actions. Acceptance: includes baseline metrics, tuning actions, post-tuning results, and recommendations for cost or performance improvement. |
| Monthly and for major releases or performance issues. |
| 17 |
| Production Readiness Review Package |
| Evidence that the pipeline or data product is ready for production deployment. Acceptance: includes requirements, design, code, tests, security, metadata, access controls, runbook, monitoring, rollback plan, and approvals. |
| Prior to each production deployment. |
| 18 |
| Operational Runbook |
| Procedures for monitoring, restart, failure handling, escalation, data-quality exceptions, consumer issues, and recovery. Acceptance: runbook is complete enough for Government or support staff to operate the pipeline for routine issues without developer intervention. |
| For each production pipeline or data product. |
| 19 |
| Incident, Defect, and RCA Reports |
| Reports for production failures, defects, recurring issues, root causes, corrective actions, and prevention measures. Acceptance: includes issue timeline, impact, root cause, resolution, preventive action, owner, and closure status. |
| As incidents occur and as directed. |
| 20 |
| Knowledge Transfer Materials |
| Training materials, walkthroughs, office-hour materials, code explanations, architecture diagrams, and operational guides. Acceptance: supports Government staff understanding, operation, troubleshooting, and sustainment of pipelines and data products. |
| Monthly, at major releases, and before transition of support. |
| 21 |
| Weekly Status Report |
| Status of work completed, work planned, risks, issues, blockers, decisions needed, dependencies, staffing, and schedule. Acceptance: includes measurable progress against backlog, deliverables, releases, risks, and production support items. |
| Weekly. |
| 22 |
| Monthly Performance Metrics Report |
| Summary of pipeline delivery, operational health, SLA performance, defects, data-quality results, deployment activity, backlog, and risks. Acceptance: includes trend metrics and corrective actions for missed targets, recurring incidents, or delivery delays. |
| Monthly. |
| 23 |
| Key Personnel Commitment Package |
| Signed commitment letters, resumes, qualification matrices, availability certifications, and proposed level of effort for each named key person. Acceptance: each letter states that the person authorized resume use, is willing and available to perform at the proposed level of effort, and has no known conflicting commitment preventing performance. |
| With proposal and before award as directed; refreshed before start of performance if requested. |
| 24 |
| Key Personnel Baseline and Staffing Matrix |
| Contract baseline identifying each key person, role, employer, subcontractor relationship if applicable, approved level of effort, clearance or access status, start date, backup, and workstream assignment. Acceptance: matches the accepted proposal and CO-approved changes. |
| At kickoff; updated monthly and with any approved change. |
| 25 |
| Key Personnel Substitution Request Package |
| Written request for any proposed replacement, including reason for substitution, supporting documentation, proposed replacement resume, qualification comparison, availability, level of effort, impact assessment, transition plan, and no-additional-cost statement. Acceptance: complete package submitted to the CO before any substitution becomes effective. |
| At least 30 calendar days before voluntary substitution, or within 1 business day of emergency unavailability. |
| 26 |
| Key Personnel Transition and Knowledge Transfer Package |
| Transition plan and evidence for replacement or temporary backfill of any key person. Acceptance: includes overlap schedule, open work inventory, risks, decisions, credentials/access transfer, runbook updates, stakeholder handoff, and Government acceptance of transition completion. |
| For each approved substitution or extended absence. |
| 27 |
| Monthly Staffing and Availability Report |
| Report showing actual staffing, vacancies, substitutions, labor-category alignment, key-personnel availability, level-of-effort variances, onboarding status, training status, and staffing risks. Acceptance: identifies any variance from the approved staffing baseline and corrective actions. |
| Monthly, and more frequently when staffing risk is elevated. |
7. Performance Standards The contractor shall meet the following performance expectations unless otherwise directed by the Government.
| Area |
| Performance Standard |
| Requirements Traceability |
| 100% of approved pipeline requirements shall be traceable to design, code, test evidence, and deployment package. |
| Source-to-Target Mapping |
| 100% of production data products shall have approved source-to-target mapping or documented Government-approved exception. |
| Data Quality |
| 100% of production pipelines shall include approved data-quality checks, reconciliation rules, and exception handling. |
| Metadata |
| 100% of production data products shall include ownership, description, lineage, security classification, refresh frequency, and access instructions. |
| Code Management |
| 100% of production code shall be stored in a Government-approved repository with version history and deployment traceability. |
| Deployment Automation |
| Production deployments shall use approved automated or repeatable deployment processes unless an exception is approved. |
| Runbooks |
| 100% of production pipelines shall have an operational runbook before transition to steady-state support. |
| Production Readiness |
| No pipeline or data product shall be deployed to production without test evidence, security validation, metadata, runbook, rollback plan, and Government approval. |
| Defect Remediation |
| Critical production defects shall be triaged according to Government-approved severity and escalation procedures. |
| Knowledge Transfer |
| Contractor shall provide documentation and walkthroughs sufficient for Government staff to understand routine operation, monitoring, and troubleshooting. |
| Key Personnel Continuity |
| 100% of key personnel shall start on the approved date and maintain the approved level of effort unless the CO approves a substitution, reduction, or temporary backfill. |
| Substitution Control |
| No key-personnel substitution, reassignment, reduction in level of effort, or replacement is effective until approved in writing by the CO. |
| Staffing Risk Reporting |
| The contractor shall report actual or anticipated key-personnel unavailability within 1 business day of knowledge and shall provide mitigation actions. |
8. Coordination Requirements The contractor shall coordinate with Government-designated teams and stakeholders, including but not limited to:
EDP platform team.
EDP pipeline team.
Vertical application teams.
Compliance Hub and Document Matching teams.
TSOA/IOLA stakeholders.
Trump Accounts stakeholders.
Clean Energy stakeholders.
Tax Processing and legacy source-system teams.
BI teams supporting Tableau, Business Objects Enterprise, and Power BI.
API and application integration teams.
Data governance, metadata, privacy, and security teams.
Cloud, network, DevSecOps, and infrastructure teams.
Product owners, data owners, data stewards, and business consumers.
The contractor shall participate in backlog grooming, architecture reviews, design reviews, production-readiness reviews, release planning, defect triage, incident review, and stakeholder demonstrations as directed by the Government.
9. Assumptions and Dependencies
| 1. | The Government will identify priority applications, verticals, source systems, data products, and any platform port/test waves. |
| 2. | The Government will provide access to approved environments, repositories, metadata tools, source-system documentation, legacy artifacts, and stakeholder points of contact. |
| 3. | Source-system teams will provide required extracts, connectivity, schema information, copybooks, data dictionaries, job schedules, and test data as applicable. |
| 4. | BI and application teams will validate that curated data products meet reporting, dashboard, API, and analytical requirements. |
| 5. | Security, privacy, disclosure, records, and data-governance teams will provide required policy direction and approval workflows. |
| 6. | Production deployment timing will be subject to Government change-management, security, testing, and release procedures. |
| 7. | Use of AI-assisted modernization tools shall be limited to Government-approved tools, environments, data classifications, and security boundaries. |
10. Government Responsibilities
| 1. | Provide priorities, approvals, direction, and acceptance decisions. |
| 2. | Provide access to approved systems, tools, environments, repositories, and data sources. |
| 3. | Identify data owners, business owners, technical owners, product owners, and consumer representatives. |
| 4. | Provide or coordinate access to source-system documentation, legacy code, data dictionaries, copybooks, extracts, and test data. |
| 5. | Review and approve requirements, designs, data products, security controls, metadata, test results, and production releases. |
| 6. | Support resolution of cross-team dependencies that are outside contractor control. |
| 7. | Provide final approval for use of AI-assisted tools, natural-language query capabilities, and self-service analytics patterns. |
11. Contractor Responsibilities
| 1. | Provide qualified personnel with experience in enterprise data engineering, Databricks pipeline development, AWS data services, legacy data integration, BI consumption patterns, metadata, governance, DevSecOps, testing, and production support. |
| 2. | Perform work in accordance with Government-approved standards, architecture, security requirements, change-management procedures, and development practices. |
| 3. | Maintain complete and current documentation for all assigned pipelines, data products, deployments, and operational procedures. |
| 4. | Proactively identify risks, issues, blockers, defects, dependencies, and recommended mitigation actions. |
| 5. | Ensure all production-ready pipelines are secure, tested, documented, monitored, restartable, and supportable. |
| 6. | Support knowledge transfer to Government personnel to improve long-term sustainment and reduce operational dependency on contractor staff. |
| 7. | Provide and maintain key personnel in accordance with Section 12 and the accepted proposal. |
12. Key Personnel, Staffing Continuity, and Substitution Controls
12.1 Key Personnel Positions
The Government may designate key personnel by role, workstream, labor category, or task order. Key personnel should be limited to positions that materially affect successful performance, source-selection risk, and continuity of critical technical knowledge. Unless otherwise specified in the solicitation or task order, the following positions are recommended as key personnel for this requirement:
Data Pipeline Technical Lead.
Senior Databricks Data Engineer or Senior Data Engineers assigned to critical pipeline workstreams.
Legacy Data Modernization / Mainframe Integration Lead.
Data Governance, Metadata, and Data Quality Lead.
DevSecOps / Deployment Automation Lead.
BI and Semantic Layer Lead, when BI consumption or semantic modeling is in scope.
AI / Natural-Language Query Enablement Lead, when AI or self-service analytics work is in scope.
Production Support / Site Reliability Lead, when operations and maintenance support is in scope.
The Contracting Officer may designate additional or fewer key personnel based on the final acquisition strategy, task-order scope, period of performance, and evaluation approach.
12.2 Government Furnished Property (GFP) and Government Furnished Information (GFI) Government furnished property (to include material, equipment, and/or information) shall be provided in the performance of this contract. The IRS will provide the following property:
| ITEMS |
| QUANTITY |
| Contractor Identification Badge |
| TBD |
| Laptop Computer with Local Area Network Access and standard office automation software |
| TBD |
| Office Space (if requested) |
| TBD |
Government furnished information (including manuals, notes, memos, instruction materials, and other information) shall be provided during the performance of this agreement. The IRS will provide the following information:
| ITEMS |
| QUANTITY |
| Manuals, directives, instructions, and other printed/electronic media required for the performance of duties including IRM and other official use only publications |
| TBD |
12.3 Materiality of Key Personnel
The contractor's proposed key personnel are material to the Government's evaluation, source-selection decision, award decision, and assessment of performance risk. The contractor shall provide the named key personnel identified in the accepted proposal and incorporated into the contract at the level of effort, role, and start date approved by the Contracting Officer.
The contractor shall not treat proposed key personnel as interchangeable labor resources after award. Reassignment to another contract, internal project, business development activity, corporate initiative, or lower-priority task shall not reduce the approved level of effort for this contract unless approved in writing by the Contracting Officer.
12.4 Key Personnel Commitment Letters and Availability Certification The offeror shall submit a signed commitment letter for each proposed key person. Each letter shall be signed no earlier than the date specified in the solicitation and shall state that the individual:
Authorizes the offeror to use the individual's resume and qualifications in the proposal for this requirement.
Is willing and available to perform the proposed role at the proposed level of effort upon award and through the required performance period, subject only to circumstances outside the individual's or contractor's reasonable control.
Understands that the Government may rely on the individual's qualifications, experience, commitment, and availability in evaluating the proposal and making the award decision.
Has disclosed to the offeror any known conflicting commitment that would prevent performance at the proposed level of effort.
The offeror shall certify that it has a reasonable basis to expect that each proposed key person will be available to perform the contract as proposed. The offeror shall promptly notify the Contracting Officer if, before award, any proposed key person becomes unavailable or the offeror no longer has a reasonable basis to expect that the person will perform.
12.5 Restriction on Substitution, Reassignment, and Reduced Level of Effort The contractor shall not remove, replace, substitute, reassign, or reduce the approved level of effort of any key person without prior written approval from the Contracting Officer. No substitution, reassignment, or level-of-effort reduction is effective until approved in writing by the Contracting Officer. Approval by the Contracting Officer's Representative, program office, technical monitor, task lead, or other Government personnel does not constitute approval for purposes of this section.
For the first 180 calendar days after award or start of performance, whichever is later, the contractor shall not propose a voluntary substitution of key personnel except for circumstances outside the contractor's reasonable control or when removal is directed or approved by the Government. Business convenience, internal reassignment, competing contractor priorities, post-award recruiting failure, or use of the individual on another contract shall not be considered sufficient basis for voluntary substitution during this initial period.
12.6 Notice of Actual or Anticipated Unavailability
The contractor shall notify the Contracting Officer and Contracting Officer's Representative within 1 business day after learning that a key person is unavailable, may become unavailable, may be unable to perform at the approved level of effort, or may not start on the approved start date. The notice shall include the reason for actual or anticipated unavailability, affected workstreams, immediate mitigation steps, and the expected date for a formal substitution or backfill package, if required.
For a voluntary substitution or planned reduction in level of effort, the contractor shall submit a complete substitution request package at least 30 calendar days before the proposed change. For emergencies or circumstances outside the contractor's reasonable control, the contractor shall submit the package as soon as practicable and no later than 5 business days after the initial notice, unless the Contracting Officer approves a different schedule.
12.7 Required Substitution Request Package
A key-personnel substitution request shall include, at a minimum:
Name, role, employer, proposed start date, proposed level of effort, and availability of the proposed replacement.
Detailed explanation for the substitution, including supporting documentation when available.
Current resume of the proposed replacement.
Qualification matrix comparing the proposed replacement against the solicitation minimum requirements, the accepted proposal…
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