Senior Data Engineer

Location: Forth, TX — On-site, face-to-face mandatory Duration: Long term Responsibilities Architect, develop, and maintain ETL/ELT pipelines using Azure Databricks, ADF, and Snowflake. Implement scalable batch and streaming data processing solutions with PySpark/Scala. Design and optimize SQL for data modeling, transformations, and analytical workloads. Integrate diverse data sources (cloud, on-premises, APIs) and ensure data quality, lineage, and observability. Collaborate with solution architects, product owners, and analytics teams to convert business requirements into technical designs. Apply best practices for data governance, security, performance tuning, and monitoring. Lead incident response, root cause analysis, and remediation for production issues. Produce clear technical documentation and operational runbooks. Required Qualifications Minimum 5 years of professional data engineering experience. Proven expertise with Databricks (Azure Databricks preferred). Strong experience with Microsoft Azure data services, including ADF, ADLS/Blob Storage; Synapse experience is a plus. Hands-on experience with Snowflake: schema design, performance optimization, security controls. Advanced SQL skills and experience with both normalized and denormalized schemas. Proficiency in Python and PySpark; Scala experience is advantageous. Familiarity with CI/CD for data pipelines and infrastructure-as-code (Terraform/ARM/Bicep). Solid understanding of data governance, metadata management, and security best practices. Strong analytical, communication, and collaboration skills. Eligibility: U.S. Citizen, H4 EAD, or GC EAD only. Preferred Qualifications Experience with streaming technologies (Structured Streaming, Kafka). Exposure to BI tools such as Power BI or Tableau. #J-18808-Ljbffr BrezQ