Data Engineer

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.

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.

• 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.

• 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 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.

• 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.

• 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 necessary 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 the data and technical artifacts necessary for transition to Government self-sustaining operations.

• 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…