Azure Data Engineer - Databricks / Microsoft Fabric - Only near by to Houston, TX

Data Engineer Azure / Databricks / Microsoft Fabric
The Woodlands, TX (Locals)

Only near by to Houston, TX

Work Arrangement: Four days in office Monday through Thursday, Friday Remote

We are looking for an experienced Data Engineer to join our team for an initial 6-month contract, with the possibility of extension. This role will support data engineering needs across multiple initiatives and help accelerate the delivery of existing project backlogs.

Key Responsibilities & Skills

• Develop and support scalable data pipelines using Azure Databricks, including Unity Catalog, Delta Lake, PySpark, and Lakeflow/DLT.
• Build and manage Databricks Asset Bundles and CI/CD processes for data engineering deployments.
• Design and implement Microsoft Fabric solutions using Lakehouse, OneLake, Data Pipelines, and Dataflows.
• Work with Fabric networking concepts such as Managed Private Endpoints and VNet Gateways.
• Develop production-grade data pipelines using Python and SQL.
• Apply dimensional modeling and Medallion Architecture (Bronze/Silver/Gold) principles.
• Experience with dbt is preferred.
• Integrate data from REST APIs, ERP and legacy platforms such as JDE, DB2/IBM i, Oracle P6, or similar systems.
• Utilize Azure integration services including Durable Functions, Logic Apps, and Service Bus.
• Implement CI/CD using Azure DevOps or GitHub.
• Apply Infrastructure as Code using Bicep or Terraform.
• Work with service principals, workload identity federation, and environment promotion strategies.
• Support downstream analytics through Power BI and semantic models, including Direct Lake.
• Apply best practices for semantic model governance and enterprise BI data serving.
• Experience with Power Platform / Dataverse is a plus.

Ideal Candidate

The ideal candidate will have strong hands-on experience across Azure Databricks, Microsoft Fabric, SQL, Python, cloud data integration, DevOps, and Infrastructure as Code, with the ability to work across multiple data initiatives in a fast-paced enterprise environment.