Data Engineer

About the Role

As FWI’s Data Engineer on the DA2I program, you’ll collect, clean, and transform raw data into the trusted, well-governed datasets that power financial management decisions across the Department of War. This role supports the Department of War Comptroller and plays a crucial role in building and maintaining reliable datasets and analytics pipelines.

Work Schedule and Location

• Hybrid role based in Arlington, Virginia.
• Typically 1–2 days on site per month, with the balance remote.
• Requires someone in the National Capital Region to be on site when the mission calls for it.

Key Responsibilities

• Collect, clean, and transform raw data into meaningful, actionable information.
• Help implement analytical techniques and applications that use data-oriented programming languages, visualization tools, and modern computational methods.
• Apply foundational data mining, data modeling, natural language processing (NLP), and machine learning techniques to extract insights from large structured and unstructured datasets.
• Visualize, interpret, and clearly report data findings, occasionally developing dynamic or automated data reports for stakeholders.
• Analyze data patterns and validate data quality to keep information accurate and reliable.
• Assist with troubleshooting data workflows and support senior data scientists in maintaining stable, well-governed analytics pipelines.
• Improve data availability, transparency, and mission-critical decision-making across enterprise systems.

Requirements & Tech Stack

• Foundational experience using Python, SQL, R, or similar languages for data manipulation, ETL, or analytics workflows.
• Exposure to data-processing frameworks or platforms (e.g., Databricks, Spark, or equivalent).
• Familiarity with mapping raw-to-scrubbed data stages.

Qualifications

• Up to 3 years of directly related experience.
• B.A./B.S. degree.
• Understanding of basic analytical concepts such as data mining, machine learning fundamentals, NLP techniques, and data modeling.
• Ability to perform data validation, identify anomalies, and support data-quality governance under guidance from senior team members.
• Ability to interpret trends, visualize results, and communicate data findings using dashboards and modern visualization tools.
• Active Secret clearance.

Desired

• Exposure to mission-focused analytics platforms and large-scale enterprise datasets.
• Familiarity with audit workflows, financial data environments, or systems involving structured and semi-structured data integrations.
• Experience collaborating with cross-functional teams and translating business requirements into basic analytical or software tasks.
• Experience building lightweight scripts or prototypes that automate small analytical tasks or data transformations.