Senior Data Engineer

Location:
Forth, TX — On-site, face-to-face mandatory

Duration:
Long term

• 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.

• 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.

• Experience with streaming technologies (Structured Streaming, Kafka).
• Exposure to BI tools such as Power BI or Tableau.