Data Engineer (Advanced Analytics)

Data Engineer (Advanced Analytics)

Location: Springfield/Alexandria, VA | Clearance: Active TS/SCI Required

The Role

As a Data Engineer for the Program Execution Office - Advanced Analytics (PEO-AA), you will be the architect of the program’s data foundation. You will lead the integration of complex datasets and build the ETL pipelines that power our next-generation visualization products. Working at the management level, you will ensure that data is not just "stored," but transformed into a secure, high-value asset that tells a clear story to leadership.

Key Responsibilities

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  Data Integration Leadership: Lead engineering tasks for current and future visualization products, ensuring seamless data flow across the enterprise.
  
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  Infrastructure Management: Oversee daily data engineering activities for the core toolset, including JIRA, Confluence, and Tableau.
  
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  Advanced Scripting: Develop and maintain Python scripts to automate tasks and enhance the functionality of analytical dashboards.
  
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  Standardization & Governance: Integrate disparate datasets into a unified structure, implementing improved data governance to ensure high-integrity decision metrics.
  
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  Agile Collaboration: Work with the Agile Management Team (AMT) to optimize system operations, resource utilization, and capacity planning.
  
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  Strategic Advisory: Provide guidance and technical direction to RTM teams, helping users navigate and leverage the data systems you build.
  

Required Qualifications

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  Clearance: Must possess an active TS/SCI.
  
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  Education: Bachelor’s degree in Mathematics, Computer Science, Information Systems, or a related technical field.
  
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  Experience: 5+ years of relevant data engineering experience.
  
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  Programming: Advanced proficiency in Python (specifically for data science and automation).
  
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  Data Tools: Mastery of SQL, relational databases, and the ETL (Extract, Transform, Load) process.
  
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  Visualization: Demonstrated experience developing and modifying Tableau dashboards, including integration with JIRA/Confluence.
  
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  Technical Stack: Familiarity with PySpark and Jupyter Notebooks.
  

Preferred Skills

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  Experience exploring and establishing connections to undocumented APIs to unlock new data sources.
  
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  Strong background in data normalization and building foundations for advanced analytical tools.