What are the responsibilities and job description for the Databricks Data Engineer @ Spring, TX (Onsite - NEED LOCALS) - W2 Only, ANY VISA position at HYR Global Source Inc?
Role: Databricks Data Engineer
Location: Spring, TX - 77389 (Onsite) - NEED LOCALS
Duration: 12 Months Extension
W2 only - ANY VISA...
Work Authorization: U.S. Citizens and Green Card Holders preferred, all valid work authorizations may apply
Education Requirement - Bachelor s Degree in: Computer Science, Information Technology, Or related field
Education Requirement - Bachelor s Degree in: Computer Science, Information Technology, Or related field
Required Skills
The Databricks Data Engineer is responsible for building and maintaining data ingestion and transformation pipelines within Databricks. This role focuses on bringing data from multiple source systems into the Lakehouse and preparing it for downstream analytics.
Key Responsibilities
Location: Spring, TX - 77389 (Onsite) - NEED LOCALS
Duration: 12 Months Extension
W2 only - ANY VISA...
Work Authorization: U.S. Citizens and Green Card Holders preferred, all valid work authorizations may apply
Education Requirement - Bachelor s Degree in: Computer Science, Information Technology, Or related field
Education Requirement - Bachelor s Degree in: Computer Science, Information Technology, Or related field
Required Skills
- 6 years experience in data engineering
- Hands-on experience with Databricks and Spark
- Strong Python and SQL skills
- Experience building ETL pipelines
- Understanding of Delta Lake and distributed systems
The Databricks Data Engineer is responsible for building and maintaining data ingestion and transformation pipelines within Databricks. This role focuses on bringing data from multiple source systems into the Lakehouse and preparing it for downstream analytics.
Key Responsibilities
- Develop and maintain data ingestion pipelines from multiple sources
- Build ETL/ELT pipelines using Databricks (PySpark, SQL)
- Implement medallion architecture (Bronze, Silver, Gold)
- Ensure data quality and validation across pipelines
- Optimize pipeline performance and scalability
- Work with structured and semi-structured data formats
- Monitor pipeline execution and resolve issues