Data Engineer (PRIME Role)

Real SoftSan Antonio, MD

About The Position

This role is for a Data Engineer with PRIME Role responsibilities, including technical leadership. The position requires a candidate who is "clearable" for a U.S. Government Security Clearance, though it is not required at the start. U.S. Citizenship is mandatory. The role involves designing and building ETL pipelines, data ingestion frameworks, and troubleshooting data pipelines and system performance. The engineer will also guide data engineering strategy, mentor other engineers, and drive innovation in data capabilities.

Requirements

  • U.S. Citizenship required
  • Candidate should be "clearable" for a U.S. Government Security Clearance
  • At least 9 years of experience in data engineering, software engineering, or related technical fields
  • Bachelors in a related field (Additional experience may be considered in lieu of a degree)
  • Strong experience designing and building ETL pipelines and data ingestion frameworks
  • Hands-on experience with Kafka, NiFi, and AWS (S3, SQS)
  • Proficiency in Java with experience in unit and integration testing
  • Solid understanding of data formats (JSON, XML, SQL schemas, compressed formats)
  • Experience troubleshooting data pipelines, system performance, and dataflow issues
  • DoD 8570 IAT II certification (or higher)

Nice To Haves

  • Candidates with Security Clearance is preferred
  • 14+ years of experience is preferred
  • Familiarity with Python, with experience in unit and integration testing
  • Experience supporting cyber or network operations environments
  • Familiarity with Agile development environments
  • Experience with Kubernetes, Docker, or containerized deployments
  • Exposure to Apache Airflow
  • Strong documentation and communication skills
  • Experience developing training materials or mentoring team members

Responsibilities

  • Designing and building ETL pipelines and data ingestion frameworks
  • Troubleshooting data pipelines, system performance, and dataflow issues
  • Guiding data engineering strategy and architecture decisions
  • Mentoring engineers and promoting best practices
  • Driving innovation across data ingestion, processing, and analytics capabilities
  • Supporting program growth and long-term technical vision
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