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Data Engineer - Mid

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Onsite

Data Engineer - Mid

NALLEY CONSULTING

Data Engineer - Mid

Skills

PythonData ScienceRData AnalysisGitHubLinuxJiraConfluence

20 days ago

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Important information


Contract type:

Permanent

Location:

Washington, DC, USA

Work mode:

Onsite

Published on:

29 September 2026

What they need


*Join the Nalley Consulting team as a Data Engineer (Data Scientist in WD).*

Position: Data Engineer (Data Scientist in WD) 
LCAT: Data Scientist Mid
Location: DIA HQ, Washington, DC

**Required clearance and polygraph:**Active TS/SCI and CI polygraph. Candidates with current CI polygraph conducted within the past 7 years highly prioritized.

Required experience/education: 2+ years of experience and bachelor's degree OR 7+ years of experience in lieu of degree 

Description

On our team, you’ll work closely with your clients to understand their questions and needs, and then dig into their data-rich environments to find the pieces of their information puzzle.

You’ll develop algorithms and systems and use the right combination of tools and frameworks to turn sets of disparate data points into objective answers to help clients make informed decisions. Ultimately, you’ll provide a deep understanding of the data, what it all means, and how it can be used.  

Required qualifications

  • 2+ years of experience with statistical and general-purpose programming languages for data analysis
  • Experience analyzing structured and unstructured data sources
  • 1+ Experience with R or Python
  • Experience using scientific methods to inform qualitative and quantitative analyses
  • Ability to work effectively in a collaborative and fast-paced environment
  • TS/SCI clearance with a polygraph.

Desired qualifications

  • Experience with VS Code, GitHub, Jira, or Confluence
  • Knowledge of DoD Intelligence processes, activities, standards, and analytic tools
  • Experience with data gathering, cleansing, and parsing
  • Ability to work in Windows and Linux OS environments
  • Bachelor's degree in Operations Research, Applied Mathematics, or Data Science.

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