Data Engineer
3 weeks ago
This team has developed a hyper-responsive capability to respond to challenging and evolving requirements to counter unconventional cyber and kinetic threats with the ability to receive, store, process, and make sense of large-scale mission data at the speed of offensive and defensive operations
This capability enhances critical national security assets' ability to quickly respond to Warfighter's counter proliferation requirements with technology solutions and services incorporating innovative approaches and the fusion of various data sources and types
Responsibilities: •Collaborate with a team of software and data engineers to address technical challenges, proactively identifying innovative approaches and implementing solutions that align with customer requirements, project needs, and mission objectives
•Process, analyze, and search through petabytes of data, developing analytics tools to enhance understanding and operationalization of intelligence-related data
•Develop algorithms utilizing geo-temporal analytics to uncover patterns within trillions of records
•Provide direct support to a Tier-One SOF customer, facilitating real-world outcomes by overcoming coding challenges in a classified environment
Qualifications: •Active DoD TS/SCI Clearance (CI Polygraph preferred)
•Minimum of 4 years' experience in computer science and/or software development
•Bachelor's Degree in Computer Science or Software Engineering
•Proficient coding skills in Python, with demonstrated ability to create custom code solutions as needed (this will be evaluated during the interview process)
•Experience with coding on Linux command line
•Experience in planning and managing new application development architecture and engineering
Preferred Qualifications: •Prior or current experience supporting Special Operations and/or Intelligence Community customers in mission-focused roles
•Familiarity with geospatial data and development of geospatial-based analytical models
•Experience with CSV, JSONL ingest to Delta Lake
•Familiarity with PySpark ingest, transforms, and aggregations
•Proficiency in Elasticsearch queries and aggregations
•Familiarity with NiFi for data transfers
•Experience with DevOps tools, particularly gitlab and ansible
•Familiarity with Neo4j or similar graph products.
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