Role: Senior Databricks Engineer
Location: Austin, TX
Duration: Long term (Multiyear)
Client: State of Texas
Interview: Two rounds
Start date: Sept 1st, 2026
The Databricks Engineer should design, develop, and optimize scalable data solutions on Databricks, leveraging PySpark or Scala for large-scale data processing. Build and maintain ingestion pipelines, Declarative Pipelines (DLT), and Medallion Architecture (Bronze, Silver, Gold) to support enterprise analytics and reporting. Develop robust data models and implement data quality, validation, and governance frameworks. Create dynamic dashboards, Databricks Apps, and analytical solutions to deliver actionable business insights. Optimize workloads, monitoring, and operational processes to ensure scalability, security, and cost efficiency.
Required Skills:
Experience required: 10 years
- Experience in IT, supporting the design, development, deployment, or delivery of technology solutions.
- Experience with Databricks, including building and optimizing ETL/ELT data pipelines using Apache Spark.
- Experience in data warehousing and dimensional data modeling (star/snowflake schemas).
- Proficiency in SQL and Python (or Scala) for large-scale data processing.
- Experience designing and developing dashboards and applications natively within Databricks (e.g., Databricks SQL dashboards, Databricks Apps).
- Experience implementing data governance, data quality, and data security practices.
- Experience implementing Lakeflow Declarative Pipelines (formerly Delta Live Tables/DLT) for building and managing production data pipelines.
- Experience with Delta Lake, medallion architecture (bronze/silver/gold layers), data lakehouse design, and creating and scheduling offline jobs using Lakeflow Jobs (formerly Databricks Workflows) or similar orchestration tools (e.g., Airflow).
- Excellent communication skills, both verbal and written, including presenting insights to technical and business stakeholders.
- Experience working in public sector or state government environments.
- Databricks certification (e.g., Databricks Certified Data Engineer Associate/Professional).
- Experience with CI/CD practices for data pipelines (DevOps, Git-based workflows).
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