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Clarity Innovations

Data Engineer

MacDill AFB, FL$76k–$180kmidAdded today

About this role

Clarity Innovations seeks a Data Engineer to support U.S. Special Operations Command (SOCOM) at MacDill AFB, focusing on data governance and modernization. You'll design and maintain data pipelines, optimize databases, and integrate complex data sources to enable the command's intelligence operations.

What you'll do

  • Develop and maintain data infrastructure for transforming structured and unstructured data from multiple sources
  • Build and optimize ETL pipelines using SQL, NoSQL, and big data frameworks like Spark, Hadoop, and Kafka
  • Design complex queries and manage databases including MongoDB, Cassandra, Neo4j, and GraphDB for performance optimization
  • Administer cloud computing and CI/CD pipelines across Azure, Google Cloud, and AWS
  • Apply distributed systems principles including fault-tolerance, consistency, and consensus algorithms
  • Collaborate with product, data, and design teams to address technical infrastructure needs

What they're looking for

  • SQL and NoSQL database design and management
  • ETL pipeline development and optimization
  • Big data frameworks (Spark, Hadoop, Hive, Pig, Kafka)
  • Cloud platforms (AWS, Azure, Google Cloud)
  • API design and integration
  • CI/CD pipeline administration
  • Distributed systems architecture
  • Git operations and Agile development
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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.

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Likely interview questions

  • Describe your experience designing and optimizing ETL pipelines for large-scale data sources—what frameworks did you use and what performance improvements did you achieve?
  • How have you applied distributed systems principles like fault-tolerance and consensus algorithms in production environments?
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