Data Engineer
$120,000–$130,000 year
HybridWashington, District of Columbia, United States or Washington, United States
Job Summary
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 while meeting 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
- Must be able to pass a federal background investigation prior to starting work and maintain eligibility throughout the engagement
- Candidates must be authorized to work in the United States without current or future employer sponsorship
Desired Qualifications
- AWS Certified Data Engineer – Associate
- AWS Certified Developer – Associate
- AWS Certified Solutions Architect – Associate
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