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Anavation

ETL Software Engineer

Chantilly, VA$90.4k–$201.6kfull timemidAdded today

About this role

AnaVation seeks an ETL Software Engineer with a Top Secret clearance to design and optimize data pipelines for the Intelligence Community. You'll build robust ETL/ELT systems using Python, SQL, and modern data technologies in a mission-driven, collaborative environment.

What you'll do

  • Design, develop, and maintain ETL/ELT pipelines using Python and SQL
  • Optimize SQL queries and relational database performance across Oracle, PostgreSQL, MySQL, or MSSQL
  • Integrate Elasticsearch or OpenSearch for data indexing and search capabilities
  • Implement data quality, validation, and monitoring frameworks
  • Manage containerized deployments using Docker in Linux environments
  • Collaborate with cross-functional teams using Agile Scrum methodologies

What they're looking for

  • Python development (3+ years ETL focus)
  • SQL query optimization and relational databases
  • ETL/ELT pipeline design and implementation
  • Elasticsearch or OpenSearch
  • Docker containerization
  • Linux administration
  • Git version control and collaborative coding
  • Bash scripting

Benefits

  • Generous medical, dental, vision, and disability insurance coverage
  • 401(k) with match and 100% immediate vesting
  • Competitive pay and generous paid leave
  • Tuition and training reimbursement
  • Life and AD&D insurance
  • Top-tier work environment and collaborative team
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Anavation

Anavation builds technology solutions for government and federal agencies, including cloud infrastructure, security systems, data engineering, and custom applications. The company is hiring Security Engineers, Data Engineers, ServiceNow Developers, Systems Integration Engineers, and Full Stack Software Engineers to support mission-critical systems and cybersecurity initiatives.

View all jobs at Anavation

Likely interview questions

  • Walk us through your experience building ETL pipelines in Python—what was your largest or most complex project?
  • How do you approach SQL query optimization when dealing with large datasets?
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