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Captivation Software

Software Engineer 3 - Linux/Bash/Python/Apache Airflow/SQL/Jupyter Notebook/NumPy/JSON

Annapolis Junction, MD$130k–$270kmidAdded today

About this role

Senior software engineer needed to design and optimize data pipelines and distributed processing systems using Apache Spark and Airflow. This role requires expertise in dataflow architecture, data transport mechanisms, and building scalable analytics infrastructure for mission-critical government applications.

What you'll do

  • Design and implement efficient data ingress/egress pathways for analytics workloads
  • Architect and optimize Apache Spark-based distributed processing solutions
  • Develop and manage Apache Airflow DAGs for workflow orchestration and scheduling
  • Build data validation and quality assurance mechanisms
  • Develop automation scripts using Bash and Python for data processing tasks
  • Collaborate on complex data pipeline solutions involving multiple data formats and sources

What they're looking for

  • Linux CLI and command-line tools
  • Bash scripting and automation
  • Python and Java software development
  • Apache Airflow (DAGs, scheduling, operators, sensors)
  • Apache Spark distributed processing
  • SQL (MySQL, MariaDB, PostgreSQL)
  • Data wrangling with pandas and NumPy
  • Git version control
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Captivation Software

Captivation Software builds high-performance computing and secure analytics infrastructure for mission-critical government programs, specializing in HPC testing, enterprise dataflow architectures, and cleared defense systems. The company is hiring senior test engineers, systems engineers, and technical leaders with deep expertise in Linux, cloud infrastructure, and security clearances to validate systems and architect solutions for intelligence community operations.

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Likely interview questions

  • Describe your experience designing Apache Airflow DAGs—what challenges have you faced with complex scheduling and monitoring?
  • Walk us through a project where you optimized data pipelines using Spark. What performance improvements did you achieve?
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