Analytics Engineer

Data Engineer & Analyst - Federal Analytics Consulting Location: Washington, DC Metro Area OR Northern Virginia area (Ashburn/ Reston/ etc- Hybrid (3 days remote / 2 days on-site) Employment Type: Contract-to-Hire, converting to full-time as you prove yourself Eligibility: U.S. Citizenship required (client requirement; may involve additional suitability/clearance processing) Why This Role Most data roles keep you three steps removed from the people who actually use your work. This one doesn't. You'll sit with federal stakeholders, understand the mission they're driving toward, and build the pipelines and insights that move it forward - work with a direct, visible line to outcomes that matter to real citizens. We're hiring a Data Engineer and Analyst who's equally at home writing production-grade Python and Spark as they are standing in front of a client explaining why a trend in the data should change how they operate. You won't just execute tickets - you'll be trusted to dig into a client's data, spot the opportunity they hadn't thought to ask for, and make the case for it. This is a contract-to-hire position on a hybrid schedule (3 days remote, 2 days on-site in the DC metro area), with conversion to full-time - health insurance, 401(k), and all - once you've shown you're a fit. What You'll Do Design and build custom data pipelines and ETL/ELT processes in Python and Apache Spark Write clean, well-documented, production-grade code across diverse source systems Dig into large, complex datasets to surface trends, anomalies, and insights tied to the client's mission Build dashboards and visualizations that make findings land with technical and non-technical audiences alike Turn analysis into plain-language narratives - not just what the data shows, but why it matters and what to do next Partner directly with federal stakeholders to understand their processes, systems, and pain points Proactively pitch creative, high-value uses of data beyond the immediate ask Troubleshoot data quality issues, pipeline failures, and performance bottlenecks Document designs and decisions clearly for engineers and non-engineers alike Collaborate with a multidisciplinary, agile delivery team What You Bring 3+ years hands-on with Python for data engineering, scripting, or analysis 3+ years hands-on with Apache Spark (PySpark or Spark SQL) at scale Strong SQL and experience across relational and/or distributed data systems Data modeling chops - dimensional/star schema, normalization, ER design Comfort across a mix of database technologies (e.g., PostgreSQL, SQL Server, Oracle, MongoDB, Cassandra, DynamoDB) A track record of building visualizations that make data's implications clear to a non-technical audience Strong written and verbal communication in English - you can hold your own in a room with a client stakeholder Bachelor's degree in CS, Data Science, Information Systems, Engineering, or a related field - or equivalent practical experience Genuine curiosity and the ability to get up to speed fast in a new business domain Comfort owning ambiguous problems and driving them to delivery U.S. citizenship required Based in, or willing to relocate to, the Washington, DC metro area , with availability for on-site work Comfortable operating within the compliance and process rigor of federal engagements Nice to Have Hands-on Databricks experience in Azure, AWS, or Google Cloud Platform Cloud-native data services (Azure Data Factory, AWS Glue, S3/ADLS, Delta Lake) BI/visualization tools like Power BI or Tableau Prior federal-client or consulting experience Familiarity with federal data governance/compliance (FISMA, FedRAMP) An active Public Trust determination or federal clearance - a plus, not a requirement Who We're Looking For Someone who wants to know why the data looks the way it does, not just what it says. Someone who'd rather propose a better approach than quietly execute the one they were handed. Someone who can move from a terminal to a client meeting without missing a beat - and who takes real pride in work that's both technically sound and genuinely useful to the people who depend on it.

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