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# Data Engineer / Developer - Python & SQL

- **Company:** BRITE CONSULTING LLC
- **Location:** Mundelein, IL, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Data Analysis, Computer Programming, Continuous Integration, Data Architecture, Information Engineering, Data Governance, Data Infrastructure, Data Integration, Extract Transform Load (ETL), Data Transformation, Data Systems, Data Warehousing, Relational Databases, Apache Hive, Python (Programming Language), Power BI, Standard Sql, Software Engineering, SQL Databases, Systems Integration, Tableau (Software), Azure Data Factory, Snowflake, Palantir Foundry, Apache Spark, Backend, Git, Build Management, Data Lakes, Pyspark, Qlikview, Software Version Control, Data Pipelines, Databricks, Programming Languages
- **Published:** November 3, 2026
- **Apply:** https://www.thejobnetwork.com/job/2b9a2f10-72b6-4474-9a87-93356e7a7a7f/data-engineer-developer-python-sql

## About the Role

The ideal candidate will have strong hands-on experience working with SQL, Python or similar development technologies, data pipelines, data transformation, and complex enterprise datasets. This individual will serve as a key technical resource helping the team understand data requirements, design and build scalable solutions, troubleshoot technical and data-quality issues, and develop trusted data products for downstream analytics and reporting., * 3+ years of experience in data engineering, software development, analytics engineering, ETL development, data integration, or a related technical field.
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 * Strong proficiency in SQL, including complex joins, transformations, aggregations, and working with relational data.
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 * Hands-on development experience with Python or another relevant programming or data-development language.
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 * Experience building and maintaining data pipelines, integrations, automated data processes, or backend data solutions.
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 * Strong understanding of relational data, data transformation, data modeling, and data-quality concepts.
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 * Experience working with large and complex enterprise datasets.
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 * Ability to troubleshoot code, data pipelines, transformations, and data-quality issues.
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 * Demonstrated ability to assess an existing data environment and help determine an appropriate technical solution or architecture.
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 * Experience gathering technical requirements and translating business needs into technical solutions.
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 * Ability to learn unfamiliar technologies, platforms, and development environments quickly.
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 * Strong analytical, troubleshooting, and root-cause analysis capabilities.
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 * Strong communication and collaboration skills.
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 * Ability to work independently while supporting a larger development team.
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 * Must be able to pass a government security background check.
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 * Authorization to work in the United States is required; visa sponsorship is not available at this time.
\n, * Experience developing data solutions in Databricks.
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 * Experience with PySpark, Apache Spark, Spark SQL, or Databricks SQL.
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 * Experience with Palantir Foundry, Snowflake, Azure data services, AWS, or another modern cloud data platform.
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 * Experience with Delta Lake, data lakes, data warehouses, or lakehouse architecture.
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 * Experience implementing Bronze, Silver, and Gold data architectures.
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 * Experience with Databricks notebooks, jobs, workflows, or Lakeflow Jobs.
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 * Familiarity with Unity Catalog, data governance, permissions, and lineage.
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 * Experience with Git-based version control, collaborative development, testing, and CI/CD practices.
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 * Experience integrating data products with Qlik, Tableau, Power BI, or other BI platforms.
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 * Previous experience working within the War Data Platform (WDP) or another Department of Defense data environment., * 3+ years of relevant professional experience, including hands-on data engineering, software development, ETL development, data integration, or similar technical work.

## Description

The successful candidate should be comfortable working through ambiguous data challenges, evaluating existing data sources and processes, recommending a technical path forward, and then building the solution. The developer will work closely with data engineers, analysts, functional SMEs, developers, and business stakeholders to translate requirements into reliable, maintainable, and efficient solutions.