Washington, DC metro area (hybrid/remote considered)
About the Role
We’re looking for a Data Engineer to design, build, and optimize ETL pipelines that ingest and transform priority datasets into an enterprise data platform, using AWS-native services within a Medallion (Bronze–Silver–Gold) architecture, for a federal government client.
Key Responsibilities
- Design, build, test, and deploy ETL pipelines using AWS-native services or approved third-party tools hosted on AWS
- Develop supporting data models, schemas, validation frameworks, and database structures; enhance models to support expanded analytics and reporting
- Implement scalable data validation and quality checks, including error handling and lineage capture
- Produce complete technical documentation including ERDs, data dictionaries, and pipeline specifications
- Collaborate with stakeholders to prioritize datasets, define sequencing, and identify phased deployment options
- Support thorough testing across development, staging, and production environments
- Meet defined performance standards for pipeline reliability, data-validation pass rates, and data freshness
Required Qualifications
- 3–7+ years designing and maintaining AWS-based data pipelines (Glue, Lambda, Step Functions, S3)
- Experience building serverless, event-driven ETL/ELT workflows and Medallion/Lakehouse designs
- Proficiency in Python, SQL, PySpark, Pandas, or similar data processing frameworks
- Experience with data validation tools (e.g., Great Expectations), data catalogs (AWS Glue, Lake Formation), CI/CD, and infrastructure-as-code (Terraform)
- Experience producing technical documentation (ERDs, data dictionaries, lineage diagrams) for government or regulated stakeholders
Preferred Certifications
- AWS Certified Data Engineer – Associate
- AWS Certified Developer – Associate
- AWS Certified Solutions Architect – Associate
Additional Requirements
Must be able to pass a federal background investigation prior to starting work and maintain eligibility throughout the engagement.
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