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Accenture Federal Services

Forward Data Engineer

McLean, VAFrom $265.3kmidAdded 1 month ago

About this role

Accenture Federal Services seeks a Forward Data Engineer to design and optimize data pipelines for US federal government clients using modern cloud technologies like Spark, Apache Iceberg, and Kubernetes. You'll ensure data integrity, collaborate across teams, and maintain data services while supporting national security and defense missions.

What you'll do

  • Design and optimize data pipelines using Spark, Apache Iceberg, EMR, and Kubernetes
  • Maintain data pedigree and provenance while protecting data access
  • Clean and preprocess data for advanced analytics use
  • Collaborate with enterprise groups on data standards and engineering teams on service updates
  • Conduct quarterly analysis and recommend data tools for new environments
  • Provide administration and performance tuning support for data tools

What they're looking for

  • Data lifecycle engineering
  • ETL tool development and maintenance
  • Python and SQL programming
  • Apache Spark
  • Cloud and on-premises data solutions
  • COTS and open-source tools (ElasticSearch, NiFi)
  • Palantir Foundry
  • Agile/Scrum methodologies

Benefits

  • Recognized as Glassdoor Top 100 Best Place to Work
  • Collaborative and inclusive community
  • Professional certifications and industry training
  • Hands-on learning and growth opportunities
  • Competitive compensation ($130,200–$265,300 in select states)
  • Comprehensive benefits package
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Accenture Federal Services

Accenture Federal Services builds and maintains mission-critical technology solutions for the U.S. federal government, including cloud infrastructure, enterprise systems integrations, and cyber defense tools. The company is hiring DevOps engineers, full-stack developers, SAP specialists, and test engineers to support classified and unclassified federal government projects.

View all jobs at Accenture Federal Services

Likely interview questions

  • Walk us through your experience designing and optimizing data pipelines using Spark and Apache Iceberg—what challenges did you encounter and how did you solve them?
  • Describe your experience with ETL tool development and maintenance. Which tools have you worked with, and how did you approach performance tuning?