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ACT1 Federal

Senior Data & Analytics Engineer

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Position Title: Senior Data & Analytics Engineer

Location: Pentagon, Arlington, Virginia

Category: Funded

Schedule (FT/PT): Full Time

Travel Required: May require occasional domestic travel

Shift: Day

Remote Type: In-Office

Clearance required: Current Top Secret. Sensitive Compartmented Information (SCI) eligibility

Salary: $180,000 - $210,000

Who is ACT1 Federal? ACT1 Federal LLC is a 100% employee-owned company. We’ve served the Department of War (DoW) for nearly thirty years. Our core missions include weapon systems engineering, logistics, space domain expertise, global defense and security, business and financial management for security assistance and major defense articles, as well as military training and arctic security. Join us!

Description: ACT1 Federal is seeking an experienced Senior Data & Analytics Engineer to provide senior-level data-engineering, data-architecture, analytics-engineering, and business-intelligence support to the Director of Data Management and Performance Assessment, Office of the Deputy Assistant Secretary of the Navy for the Defense Industrial Base (DASN (DIB)). The engineer supports Department of the Navy (DON) efforts to develop governed data products and analytic capabilities supporting assessment of defense-industrial-base performance, production capacity, supply-chain risk, investment activity, and program outcomes.

The primary mission application is wartime production planning within the defense-industrial-base portfolio. The engineer develops documented data pipelines, models, semantic layers, datasets, and analytic products that support Government assessment of industrial capacity, supplier readiness, manufacturing constraints, delivery timelines, workforce trends, material availability, and surge potential.

This position requires a senior technical subject matter expert with demonstrated experience in enterprise data engineering, analytics engineering, data-platform architecture, and governed business-intelligence products. The engineer shall be capable of transforming complex, incomplete, inconsistent, or delayed source data into well-documented, analytic-ready datasets and products while clearly distinguishing verified data, analytical assumptions, limitations, confidence levels, and judgments.

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