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# Data Engineer

- **Company:** VC5 Consulting
- **Location:** Houston, TX, United States
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Information Systems, Information Engineering, Data Integration, Python (Programming Language), PostgreSQL, Microsoft SQL Server, NoSQL, Oracle (Applications), SQL Databases, Snowflake, Microsoft Fabric, Data Lakes, Pyspark, Data Analytics, Data Pipelines, Databricks
- **Published:** June 26, 2026
- **Apply:** https://www.dice.com/job-detail/4516298f-f66a-45e7-98a7-972be9540de7

## About the Role

* Minimum of 5 years of IT/technology experience spanning data analysis, data engineering, and/or data integration.
 * At least 3 years of experience writing SQL/NoSQL queries, with specific experience in MS SQL Server, Oracle, and/or Postgres.
 * Bachelor''s degree in Information Systems, IT, or a related technical discipline.
 * Hands-on experience with a modern cloud data platform or lake house, such as Databricks, Microsoft Fabric, or Snowflake.
 * Strong Python skills for data engineering, including experience with PySpark.

## Description

This role focuses on designing, developing, and supporting data engineering and data integrations, primarily in a Databricks data lake house environment. The Data Engineer will collaborate closely with business users to build semantic data models, dashboards, and perform hands-on analysis to address business questions. This position plays a crucial role in establishing a robust data foundation that supports AI and machine learning initiatives, ensuring high-quality, well-governed data products., * Design and develop reliable data pipelines that ingest data from various source systems into a Databricks data lake house.

 * Curate data through a layered medallion architecture into clean, analytics-ready datasets.
 * Collaborate with business users to build semantic data models and dashboards that support decision-making.
 * Conduct hands-on data analysis to answer business questions and provide actionable insights.
 * Establish and maintain data governance and quality practices to ensure the reliability of data products.


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