Data Engineer

Synectics for Management Decisions IncWashington, DC
$120,000 - $130,000Hybrid

About The Position

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. Job location is the Washington, DC Metro Area. Hybrid or Remote options can be considered. Position is contingent upon contract award. Join a collaborative team supporting high-impact federal programs that incorporate innovative technology solutions. You'll have the opportunity to lead complex modernization initiatives, work alongside talented technical professionals, and help shape the future of government IT and data management.

Requirements

  • 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.

Nice To Haves

  • AWS Certified Data Engineer – Associate
  • AWS Certified Developer – Associate
  • AWS Certified Solutions Architect – Associate

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

Benefits

  • Synectics is an equal opportunity employer.
© 2026 Teal Labs, Inc
Privacy PolicyTerms of Service