Principal Java Data Engineer
Tasks
- Collaborate with product, analytics, and AI teams
- Define SLAs and SLOs for latency and throughput with alerting and dashboards
- Define schema contracts and enforce backward compatible schema evolution
- Develop and maintain data platform services using Java microservices
- Drive data governance observability and performance tuning
- Embed peer review quality feedback
- Engineer and optimize batch and real time data pipelines
- Establish observability with metrics logging and distributed tracing
- Implement event driven and cloud native modernization
- Implement transformation tests data assertions and automated pipeline checks
- Lead design and implementation of scalable distributed systems
Perks/Benefits
- Allyship and inclusion communities
- Caregiver leave
- Continuous development support program
- Employee assistance program
- Employee recognition
- Flexible paid time off
- Parental leave
- Retirement plan matching
- Wellness support programs
Skills/Tech-stack
AWS | Apache Hudi | Apache Trino | Azure | Azure Data | Azure Data Lake | Azure Data Lake Storage | Azure Data Lake Storage Gen2 | CI/CD | Containerization | DBT | Data Governance | Data Lake Storage Gen2 | Data Pipelines | Data Quality | Databricks | Distributed Systems | Distributed tracing | Docker | Event Driven | Event-driven architecture | GCP | Great Expectations | HDFS | Java | Kubernetes | Lakehouse | Logging | Metrics | Microservices | Observability | Performance Tuning | Schema evolution | Spark
Education
N/A
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