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Accenture Federal Services

Data Engineer (Onsite Vandenberg, CA)

Point Mugu, CAFrom $176.2kmidAdded 1 month ago

About this role

Accenture Federal Services seeks an experienced Data Engineer to design and maintain scalable data pipelines and solutions using Palantir Foundry for US federal defense and national security clients. This onsite role at Vandenberg, CA requires 7+ years of experience with Python, ETL processes, and data quality management.

What you'll do

  • Design, build, and maintain scalable data pipelines in Palantir Foundry
  • Implement ETL processes for data migration and deployment
  • Ensure data quality across systems and monitor pipeline performance
  • Collaborate with cross-functional teams to identify data requirements
  • Develop subject-matter expertise and work independently
  • Participate in team problem-solving discussions

What they're looking for

  • Python (advanced proficiency)
  • Palantir Foundry
  • ETL processes and data pipelines
  • Data quality assurance
  • Cloud computing
  • Unstructured data manipulation
  • Database management
  • Open-source tools and machine learning

Benefits

  • Glassdoor Top 100 Best Place to Work recognition
  • Professional development through certifications and industry training
  • Collaborative and inclusive work environment
  • Comprehensive benefits package
  • Growth and learning opportunities
  • Support for security clearance eligibility
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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 building and maintaining data pipelines in Palantir Foundry. What challenges did you face and how did you overcome them?
  • Describe your approach to ensuring data quality across complex systems. What tools or frameworks have you used?