Senior Data Engineer (AWS, Databricks)
Tasks
- Apply SDLC discipline with version control code review testing and documentation
- Create reusable engineering patterns and templates
- Design and build production data pipelines
- Embed data quality observability and lineage
- Evaluate emerging tooling and recommend standards
- Implement DataOps with CI CD and trunk based development
- Integrate AI coding tools into development workflow
- Measure and demonstrate impact of engineering changes
- Mentor and upskill engineers through code review and design guidance
- Modernize legacy Ab Initio workloads to cloud native ELT patterns
- Optimize cost and performance for data platforms
- Reduce commit to production lead time
Perks/Benefits
- 401k match
- Health insurance
- Matching gift program
- Mental health counseling
- Paid Holidays
- Paid time off
- Volunteer rewards program
- Wellness program
Skills/Tech-stack
AWS | Ab Initio | Apache Iceberg | Apache Spark | Automated testing | Branching strategy | CI/CD | Data Lineage | Data Observability | Data Quality | Data Warehousing | Databricks | Delta Lake | Dimensional Modeling | ELT | FinOps | GDE | Git | GitHub Actions | GitLab CI | Infrastructure as Code | Jenkins | Jira | Medallion Architecture | PySpark | SQL | Snowflake | Snowflake Schema | Spark SQL | Star Schema | Terraform | Trunk-based | Trunk-based development | Unity Catalog | “as-code”
Education
Roles
Regions
Countries
States
Cities
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