Principal Java Data Engineer
Tasks
- Automate data accuracy checks
- Automate data completeness checks
- Automate data freshness checks
- Define data SLAs and SLOs
- Define data quality schema contracts
- Develop event-driven architectures
- Enforce schema evolution
- Engineer data pipelines
- Establish data observability
- Implement Java microservices
- Implement data governance best practices
- Implement metrics logging tracing for streaming jobs
- Implement transformation tests
- Integrate alerting and dashboards
- Lead scalable distributed system design
- Mentor engineers
- Modernize data ecosystem
- Optimize batch and real time data solutions
- Perform peer code reviews and feedback
Perks/Benefits
- Caregiver leave
- Continuous development support program
- Employee assistance program
- Flexible paid time off
- Parental leave
- Retirement plan matching
- Wellness Support Programs and Resources
Skills/Tech-stack
AWS | Alerting | Apache Hudi | Apache Spark | Apache Trino | Azure | Azure Data | Azure Data Lake | Azure Data Lake Storage | Azure Data Lake Storage Gen2 | Batch Processing | CI/CD | Containerization | DBT | Data Freshness Testing | Data Governance | Data Lake Storage Gen2 | Data Quality | Data Validation | Data freshness | Databricks | Distributed Systems | Distributed tracing | Docker | Event Driven | Event-driven architecture | GCP | Great Expectations | HDFS | Java | Java Microservices | Kubernetes | Lakehouse | Logging | Metrics | Observability | SLA | SLO | Schema Contracts | Schema evolution | Streaming Data | Transformation Testing | Trino
Education
N/A
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