Jobs in Virginia 2026 (Now Hiring) - Smart Auto Apply

• 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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