Mid-level Data Engineer / Secret

PeratonScott AFB, IL
6d$80,000 - $128,000

About The Position

We’re seeking a highly skilled Mid-level Data Engineer to support the DPMO platform’s transition into the Advana environment. This role is ideal for someone who thrives in complex data ecosystems, enjoys building scalable solutions, and is motivated by mission-driven work that directly supports the Department of Defense. You’ll work closely with senior engineers and cross-functional teams to design, validate, and optimize data structures and pipelines that power enterprise-level analytics and decision-making.

Requirements

  • Bachelor’s degree and a minimum of 5 years of relevant experience, or a Master’s and 3 years. An additional 4 years of relevant experience may be considered in lieu of degree.
  • Experience with development and implementation of enterprise-level data science solutions.
  • Knowledge of various machine learning methods including classification, regression, time-series forecasting, neural networks, deep learning, and artificial intelligence.
  • Strong Python and SQL skills.
  • Demonstrated creative-thinker with a mission-minded focus.
  • Possess a collaborative, team-oriented mindset.
  • Ability to persist in a fast-paced, dynamic environment.
  • Demonstrated excellent oral and written communication skills.
  • U.S. citizenship required.
  • Active DoD Secret security clearance.

Nice To Haves

  • Experience with Advana and/or DataBricks.

Responsibilities

  • Develop, test, validate, update, and design data schema and data ontologies to support the DPMO platforms’ transition into the Advana environment.
  • Ensure optimized data flows from multiple sources into a distributed data storage framework by leveraging efficient, distributed data processing techniques.
  • Design and implement scalable solutions that can handle large volumes of data.
  • Perform validation testing to ensure data is complete, accurate, and correctly transformed according to business rules.
  • Confirm integrated data is usable for business needs.
  • Implement frequent data tests, health checks and alerts to enhance data accuracy and consistency.
  • Assist senior data engineers with post data integration efforts.
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