Data Engineer

E Logic; Richmond (VA); Remote; USD 57,074,000 - 95,123,000; Part time

Job summary

E-Logic, Inc. is seeking a Data Engineer to support the IRS RAAS SOI Division in discovery, preparation, validation, transformation, integration, and production processing of tax and administrative data used to produce privacy-preserving Qualified Opportunity Zone statistics.

The Data Engineer will support data profiling, data inventory and schema development, synthetic data preparation, data cleaning and validation, reproducible workflows, ETL development, production analytical pipelines,

Qualifications

• Demonstrated experience in data engineering, data processing, ETL, data validation or related technical data activities.
• Experience with complex datasets and reproducible data workflows.
• Experience developing data inventories, schemas, data dictionaries, and technical documentation.
• Experience developing or supporting production-level data pipelines.
• Experience working with Federal datasets and applicable confidentiality, security, and governance standards.
• Familiarity with Privacy Act, CIPSEA, FISMA, OMB guidance, or comparable Federal data-governance requirements.
• Experience supporting analytical tools, pipelines, dashboards, or privacy-preserving data workflows is highly desirable.
• Ability to work closely with data scientists, software developers, statistical analysts, project managers, and Government stakeholders.
• Strong documentation, troubleshooting, analytical, and problem-solving skills.

Responsibilities

• Conduct comprehensive discovery and profiling of IRS tax and administrative datasets related to Opportunity Zone investments and Qualified Opportunity Funds.
• Support data analysis involving Form 8996 and Form 8997 records.
• Identify key data elements, variable definitions, data structures, relationships, and quality limitations for OB3 reporting requirements.
• Develop and maintain data inventories, schemas, data dictionaries, and technical data documentation.
• Perform initial data cleaning, validation, transformation, and imputation testing.
• Develop reproducible data-processing workflows.
• Identify and document data-quality issues and support resolution of material discrepancies.
• Validate processed data for use in statistical modeling and privacy-preserving analytical workflows.
• Develop synthetic test data reflecting underlying population data characteristics.
• Support testing and validation of differential privacy algorithms using synthetic datasets.
• Ensure synthetic datasets contain no identifiable real taxpayer information.
• Document data-generation processes and maintain reproducibility within IRS-approved environments.
• Develop and validate production-level end-to-end ETL and data-processing pipelines.
• Integrate data engineering workflows with statistical analysis and automated output-generation processes.
• Support implementation of the Year 1 analytical framework for TY 2026 production data.
• Develop scalable and reusable data workflows for future IRS and Treasury reporting projects.
• Support automated generation of compliant aggregated statistical outputs.
• Support implementation of privacy-preserving data workflows and analytical applications.
• Provide data-engineering support for differential privacy and disclosure-avoidance processes.
• Support evaluation of data outputs across privacy parameters and reporting granularities.
• Assist with the production of datasets, tables, dashboards, and other analytical outputs while maintaining confidentiality requirements.
• Produce transparent and reproducible data-processing code and technical documentation.
• Document data sources, schemas, transformations, validation procedures, workflows, and quality controls.
• Support methodology and QA documentation aligned with SOI requirements.
• Maintain records and documentation to support reproducibility, testing, and Government review.
• Optimize data pipelines for performance, reproducibility, and scalability within IRS-approved computing environments.
• Implement improvements based on data characteristics, stakeholder feedback, and technical requirements.
• Support training, code walkthroughs, documentation, workshops, and knowledge-transfer sessions for SOI personnel.
• Help prepare data and technical artifacts for transition to Government self-sustaining operations.

Job description

Job Summary

E-Logic, Inc. is seeking a Data Engineer to support the IRS RAAS Statistics of Income (SOI) Division in the discovery, preparation, validation, transformation, integration, and production processing of tax and administrative data used to produce privacy-preserving Qualified Opportunity Zone statistics.

The Data Engineer will support data profiling, data inventory and schema development, synthetic data preparation, data cleaning and validation, reproducible workflows, ETL development, production analytical pipelines, automated output generation, documentation, testing, and optimization within IRS-approved computing environments.

Working Hours

Remote - United States

Employment Type: Part-Time Contract Assignment

Estimated Level of Effort: 690.5 hours per contract year, approximately 13.3 hours per week on average.

The actual distribution of hours may vary based on project activities, technical requirements, meetings, and deliverables.

Key Responsibilities

Data Discovery & Profiling

• Conduct comprehensive discovery and profiling of IRS tax and administrative datasets associated with Opportunity Zone investments and Qualified Opportunity Funds.
• Support data analysis involving relevant Form 8996 and Form 8997 records.
• Identify key data elements, variable definitions, data structures, relationships, and quality limitations relevant to OB3 reporting requirements.
• Develop and maintain data inventories, schemas, data dictionaries, and technical data documentation.

Data Preparation & Quality

• Perform initial data cleaning, validation, transformation, and imputation testing.
• Develop reproducible data-processing workflows.
• Identify and document data-quality issues and support resolution of material discrepancies.
• Validate processed data for use in statistical modeling and privacy-preserving analytical workflows.

Synthetic Data & Testing

• Develop synthetic test data that reflects the structure and relevant statistical characteristics of underlying population data.
• Support testing and validation of differential privacy algorithms using synthetic datasets.
• Ensure synthetic datasets contain no identifiable real taxpayer information.
• Document data-generation processes and maintain reproducibility within IRS-approved environments.

ETL & Analytical Pipelines

• Develop and validate production-level end-to-end ETL and data-processing pipelines.
• Integrate data engineering workflows with statistical analysis and automated output-generation processes.
• Support implementation of the Year 1 analytical framework for TY 2026 production data.
• Develop scalable and reusable data workflows supporting future IRS and Treasury statistical reporting projects.
• Support automated generation of compliant aggregated statistical outputs.

Differential Privacy & Analytical Support

• Support implementation of privacy-preserving data workflows and analytical applications.
• Provide data-engineering support for differential privacy and disclosure-avoidance processes.
• Support evaluation of data outputs across privacy parameters and reporting granularities.
• Assist with the production of datasets, tables, dashboards, and other analytical outputs while maintaining confidentiality requirements.

Documentation, QA & Reproducibility

• Produce transparent and reproducible data-processing code and technical documentation.
• Document data sources, schemas, transformations, validation procedures, workflows, and quality controls.
• Support methodology and QA documentation aligned with SOI requirements.
• Maintain records and documentation necessary to support reproducibility, testing, and Government review.

Optimization & Knowledge Transfer

• Optimize data pipelines for performance, reproducibility, and scalability within IRS-approved computing environments.
• Implement improvements based on data characteristics, stakeholder feedback, and technical requirements.
• Support training, code walkthroughs, documentation, workshops, and knowledge-transfer sessions for SOI personnel.
• Help prepare the data and technical artifacts necessary for transition to Government self-sustaining operations.

Qualifications

• Demonstrated experience in data engineering, data processing, ETL, data validation, or related technical data activities.
• Experience working with complex datasets and developing reproducible data workflows.
• Experience developing data inventories, schemas, data dictionaries, and technical documentation.
• Experience developing or supporting production-level data pipelines.
• Experience working with Federal datasets and applicable confidentiality, security, and governance standards.
• Familiarity with Privacy Act, CIPSEA, FISMA, OMB guidance, or comparable Federal data-governance requirements.
• Experience supporting analytical tools, pipelines, dashboards, or privacy-preserving data workflows is highly desirable.
• Ability to work closely with data scientists, software developers, statistical analysts, project managers, and Government stakeholders.
• Strong documentation, troubleshooting, analytical, and problem-solving skills.

Federal Project Requirements

• U.S. citizenship is required for this federal contract.
• Must be able to obtain and maintain the required federal clearance/security approval before receiving GFI.
• Must be eligible to receive and use an IRS laptop and contractor PIV card, as applicable.
• Must work within IRS-approved computing environments and authorized Government accounts and systems.
• Must protect FTI, taxpayer information, and other sensitive Government information.

  Work Environment & Physical Requirements

  • Fully remote position within the United States.
  • Work is performed primarily at a computer using Government-authorized systems, remote-access tools, and collaboration platforms.
  • Ability to participate in virtual technical meetings and coordinate with distributed project teams.
  • Ability to manage and document technical data workflows and processes.
  • No routine physical labor is expected.

  EEO Employer Statement

  E-Logic, Inc. is an Equal Employment Opportunity Employer and considers all qualified applicants for employment without regard to race, color, religion, sex, national origin, age, disability, veteran status, or any other status protected by applicable federal, state, or local law.