Data Engineer

Data Engineer

Data Engineer

Clearance: Active At least Interim secret or Secret clearance is required.

Pentagon (4-5 days onsite)

Job Description – Data Engineer

Role Description & Requirements

As a Mid-Level Data Engineer, this role focuses specifically on the development and
maintenance of scalable data stores that supply big data in forms needed for business
analysis.

The best athlete candidate for this position will be able to apply advanced
consulting skills, extensive technical expertise, and full industry knowledge to develop innovative solutions to complex problems. This candidate is able to work without considerable direction and may mentor or supervise other team members.

What we’re looking for:

  • Someone with a solid background developing solutions for high volume, low
    latency applications and can operate in a fast-paced, highly collaborative
    environment.
  • A candidate with distributed computer understanding and experience with SQL,
    Spark, and ETL.
  • A person who appreciates the opportunity to be independent, creative, and
    challenged.
  • An individual with a curious mind, passionate about solving problems quickly and bringing innovative ideas to the table.

Basic Qualifications:

  • 4+ years of experience with SQL
  • 4+ years of experience developing data pipelines using modern Big Data ETL
    technologies like NiFi or StreamSets.
  • 4+ years of experience with a modern programming language such as Python or
    Java.
  • 4 years of experience working in a big data and cloud environment.
  • Secret Clearance or higher.

Basic Qualifications:

  • 2 years of experience working in an agile development environment
  • Ability to quickly learn technical concepts and communicate with multiple
    functional groups
  • Ability to display a positive, can-do attitude to solve the challenges of tomorrow
  • Possession of excellent verbal and written communication skills
  • Preferred experience at the respective command with an understanding of
    analytical and data paint points and challenges across the J-Codes.