Data Engineer - DataOps
Cupertino, California, United States
USD 130K-150K Mid-level Full Time
Tasks
- Build and maintain data ingestion and transformation pipelines
- Harden and improve shared pipeline reliability
- Implement data quality checks and observability
- Maintain operational runbooks and change plans
- Manage asset lifecycle and governance
- Monitor production data product health using SLIs and SLOs
- Optimize tables storage and query performance
- Orchestrate data workflows and schedules
- Perform incident response and root cause analysis
Perks/Benefits
- 401k match
- Career growth
- Hybrid work schedule
- Medical, dental, and vision insurance
- Paid parental leave
- Paid time off
- Work-life balance
Skills/Tech-stack
Apache Airflow | Apache Iceberg | Apache Spark | CI/CD | Cause analysis | Data Quality | Data pipeline | Data pipeline management | Docker | Dremio | ELT | ETL | Git | Kafka | Lakehouse | Observability | Pipeline Management | Python | Root Cause Analysis | Root cause | SQL | Trino
Education
N/A
Roles
Regions
Countries
States
Cities
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