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Clarity Innovations

Data Engineer

Hurlburt Field, FLmidAdded today

About this role

Clarity Innovations seeks a Data Engineer to support Air Force Special Operations Command at Hurlburt Field, Florida, focusing on data integration and modernization efforts. You'll design and maintain data pipelines, optimize database performance, and collaborate with stakeholders to enable AFSOC's effective use of complex data resources.

What you'll do

  • Develop and maintain infrastructure for data transformation from structured and unstructured sources
  • Build and manage ETL pipelines using SQL, NoSQL, Spark, Hadoop, Kafka, and related frameworks
  • Create optimized queries for NoSQL and big data systems while ensuring data accessibility
  • Administer cloud computing and CI/CD pipelines across Azure, Google Cloud, and AWS
  • Apply distributed systems principles including fault-tolerance, consensus, and reliability concepts
  • Coordinate with product, data, and design teams to address data infrastructure and technical needs

What they're looking for

  • SQL and NoSQL database design and optimization
  • Data pipeline and ETL development
  • Big data frameworks (Spark, Hadoop, Kafka, Hive, Pig)
  • Cloud platforms (Azure, AWS, Google Cloud)
  • API design and integration
  • Distributed systems and performance optimization
  • Git and Agile development practices
  • Machine learning fundamentals
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Clarity Innovations

Clarity Innovations builds data engineering and software platforms for the U.S. Department of Defense and Intelligence Community, focusing on mission-critical data pipelines, ETL infrastructure, and modernization. The company is hiring Data Engineers and Software Engineers to design scalable systems, optimize databases, and support national security operations.

View all jobs at Clarity Innovations

Likely interview questions

  • Walk us through your experience designing and optimizing ETL pipelines for complex data sources.
  • Describe a situation where you had to troubleshoot performance issues in a NoSQL or big data system—what was your approach?
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