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# Secret Data Warehouse Modernization Developer

- **Company:** Insight Global
- **Location:** Fairfax, VA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Business Logic, Unit Testing, Microsoft Azure, Cloud Computing, Data Infrastructure, Extract Transform Load (ETL), Data Transformation, Data Warehousing, Dimensional Modeling, Apache Hadoop, Python (Programming Language), Microsoft SQL Server, Cloud Services, Reverse Engineering, SQL Databases, SQL Server Integration Services, SQLAlchemy, Web Application Frameworks, Data Ingestion, Snowflake, Apache Spark, Technical Debt, Git, SC Clearance, Pandas, Pyspark, Azure Synapse Analytics, Databricks
- **Published:** June 27, 2026
- **Apply:** https://www.juju.com/job/00000000gbd0o1

## About the Role

Active Secret clearance

 - Solid SQL and understanding of Kimball dimensional modeling.

 - Strong Python: Pandas, SQLAlchemy, packaging, module structure, unit testing.

 - Experience with PySpark or Spark (or willingness to ramp quickly).

 - Familiarity with cloud data platforms (Azure, AWS, etc.).

 - Experience modernizing legacy ETL systems is a major plus.

 - Ability to read, interpret, and redesign SSIS/SQL-based ETL logic.

 - Understanding of data ingestion, transformation, and structured warehouse design.

 - Experience with Git, CI/CD pipelines, and modern development practices. - Exposure to Databricks, Snowflake, or Hadoop ecosystems

 - Cloud experience (Azure or AWS)

 - Experience working in federal environments (DOJ, DEA, FBI, DHS, etc.)

 - Experience supporting both classified and unclassified systems

 - Experience with large scale or high volume data environments

 - Exposure to AI / data experimentation initiatives

## Description

Insight Global is seeking a Senior Data Warehouse Modernization Developer to support a long term federal data modernization initiative. These engineers focus on modernizing data warehouse pipeline architecture by gradually reducing reliance on SSIS and SQL-only patterns, introducing Python based ETL, improving modularity, and setting the groundwork for a future move into PySpark, distributed compute, and eventually Databricks or similar cloud platforms. They should have an in depth understanding of the Kimball model in place, and experience incrementally replacing or re platforming components. Responsibilities include:

 - Learn and understand the existing Kimball-modeled SQL Server structure over time.

 - Reverse-engineer SSIS packages and convert them into Python-based modular ETL pipelines.

 - Build reusable Python frameworks for extraction, transformation, and loading.

 - Begin introducing PySpark for scalable transformation patterns.

 - Contribute to planning a future transition path (Databricks, Azure Synapse, Snowflake, etc.).

 - Improve orchestration, dependency management, and data quality practices.

 - Identify technical debt and modernize aging ETL components.

 - Collaborate with EDW SMEs to understand business logic and lineage.

 - Build documentation and repeatable processes for modernization.


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