Senior Data Engineer-Azure/Databricks

Position Type: Full-Time A well-established Houston-based company is seeking an experienced Senior Data Engineerto join its Data & BI team and help implement and support a modern Azure cloud-based data platform. This is a hands‑on, delivery-focused role for a senior data engineer with strong experience inDatabricks, Python, Azure data technologies, and enterprise data integration. The Senior Data Engineer will build and maintain scalable Lakehouse solutions, develop ELT/ETL pipelines, integrate data from multiple enterprise systems, and help ensure the performance, security, and reliability of the company's data platform. Candidates must reside in the Houston areaand be available to work onsite at the company's Houston office as needed.

Key Responsibilities: Build, implement, and maintain scalable cloud-based data solutions using Azure and Databricks. Develop and support Lakehouse andmedallion architecturesolutions. Design and maintain ELT/ETL workflows using Databricks, Azure Data Factory, Lakeflow, and Azure Data Lake Storage. Integrate data from enterprise applications and databases, includingERP systems, Oracle, SQL Server, and other business platforms. Develop solutions using Python, PySpark/Spark SQL, Delta Lake, and SQL. Configure and maintain Databricks Unity Catalog, including access policies, metadata, and lineage. Implement data security and access controls, includingRBAC/ABAC and row- and column-level security. Monitor data pipelines, troubleshoot failures, resolve data-quality and performance issues, and support production environments. Participate in DevOps and CI/CD processes using Git, Azure DevOps and/or GitHub Actions. Develop and maintain technical documentation, including data flows, pipeline designs, runbooks, and configuration documentation. Collaborate with technical and business teams in an Agile environment.

Required Qualifications: 5+ years of hands‑on Databricks data engineering experience. Strong experience with Databricks, including Delta Lake, PySpark/Spark SQL, notebooks, jobs, and cluster management. Hands‑on experience with the Microsoft Azure data ecosystem, including Azure Data Lake Storage Gen2 and Azure Data Factory. Strong experience developingETL/ELT pipelinesand implementing Lakehouse/medallion architectures. Experience with dimensional modeling and incremental data loads. Strong database experience with Oracle and SQL Server, including PL/SQL and/or T‑SQL. Experience integrating data from enterprise applications and multiple source systems. Hands‑on experience implementing data security and access controls. Experience with Git and modernCI/CD/DevOpspractices. Working knowledge ofPower BI. Strong troubleshooting, documentation, and communication skills. Preferred Experience Experience extracting and integrating data fromJD Edwards (JDE). Experience with Databricks Unity Catalog and Lakeflow. FiveTran and/or dbt experience. Streaming technologies such as Event Hubs, Kafka, or Structured Streaming. Machine learning and AI development or deployment experience. Work Arrangement This is aHouston-based hybrid position. Candidates must currently reside in the Houston metropolitan area and be available to work onsite at the Houston office when business needs require. Candidates must be authorized to work in the United States on a permanent basis without current or future sponsorship. Third‑party and C2C submissions will not be considered. Benefitsmedical, dental and vision coverage 401(k) pension life insurance paid time off paid holidays wellness programs