United States onlyPosition Summary
We are in search of a highly collaborative and experiencedData Analyst to support the Office of Chief Data Officer (OCDO) and the Office of Performance Quality (OPQ) for a federal government contract. In this role, you will design and maintain robust data pipelines, perform in-depth analysis of large-scale datasets, and deliver actionable insights that drive mission decisions. You will work within a Databricks environment leveraging SQL, PySpark, and Python, to transform raw agency data into reliable, governed, and analytics-ready assets. The ideal candidate combines strong engineering fundamentals with analytical acumen and is comfortable operating within complex federal data environments.
Candidates must be a U.S. Citizen with the ability to obtain and maintain a government suitability clearance.
Key Responsibilities
Data Engineering & Pipeline Development
- Design, build, and maintain scalable ETL/ELT data pipelines using PySpark and Python within Databricks environments.
- Develop and optimize SQL queries, and data models to support analytical and reporting workloads.
- Automate data ingestion workflows from disparate agency sources including APIs, flat files, relational databases, and streaming feeds.
- Monitor pipeline health, resolve data quality issues, and implement alerting and logging to ensure reliability of data products.
- Collaborate with data architects to design and enforce data schemas, partitioning strategies, and performance optimization practices.
- Conduct exploratory data analysis to identify trends, anomalies, and opportunities for improvement.
- Develop self-service analytics dashboards and reports using Databricks SQL, Tableau, or Power BI.
- Write complex, performant SQL queries against large datasets to answer ad hoc analytical requests from program managers and leadership.
- Translate business questions into clearly scoped analytical tasks and deliver findings as data visualizations, written summaries, or briefings.
- Work closely with data scientists, program analysts, IT engineers, and agency stakeholders to understand data needs and deliver tailored solutions.
- Document pipelines, data models, and analytical notebooks to support knowledge transfer, peer review, and audit readiness.
- Participate in Agile sprint ceremonies, contribute to backlog grooming, and deliver iterative data products aligned with program priorities.
- Bachelor's degree in Computer Science, Information Systems, Data Science, Engineering, Mathematics, or a related technical field.
- 3+ years of experience in data engineering, data analytics, or a closely related discipline.
- Demonstrated experience on federal government programs or supporting a federal agency data environment.
- Strong proficiency in SQL — including complex joins, window functions, CTEs, and query performance tuning against large datasets.
- Hands-on experience with PySpark for distributed data processing, transformations, and optimization techniques.
- Proficiency in Python for scripting, data manipulation, and automation.
- Direct experience working within Databricks, including notebooks, jobs, clusters, and Unity Catalog.
- Familiarity with data lakehouse concepts including Delta Lake, bronze/silver/gold architecture, and medallion design patterns.
- Experience with version control systems (Git/GitHub/GitLab) and collaborative development workflows.
- Databricks Certified Associate Developer for Apache Spark or Databricks Certified Data Engineer Associate/Professional.
- Experience with cloud platforms such as AWS GovCloud, Microsoft Azure Government, or Google Cloud for Government.
- Familiarity with CI/CD practices for data pipelines, including automated testing and deployment using tools like Azure DevOps or GitHub Actions.
- Working knowledge of data visualization platforms (Tableau, Power BI) and experience connecting them to Databricks SQL endpoints.
- Familiarity with Unity Catalog for data access control, lineage, and governance within Databricks.
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