Principal Data Engineer - FLINK
Tasks
- Build stateful stream processing applications
- Configure checkpointing and fault tolerance
- Define streaming data models and schemas
- Design real-time streaming architectures
- Develop streaming data pipelines
- Ensure exactly once processing semantics
- Establish streaming platform security and compliance standards
- Govern and evolve event schemas and contracts
- Implement windowing joins aggregations and event processing
- Manage back pressure scaling and partitioning strategies
- Mentor engineers and drive streaming first design patterns
- Monitor streaming system performance and availability
- Optimize low latency high throughput pipelines
Perks/Benefits
- N/A
Skills/Tech-stack
Aggregations | Alerting | Apache Flink | Back pressure | CI/CD | Cloud Native | Cloud Native Architecture | Complex event processing | Data Contracts | Data Governance | Data Lineage | Distributed Systems | Event Processing | Event Streaming | Event time | Event-time processing | Exactly once | Exactly-once semantics | Fault Tolerance | High Availability | Infrastructure as Code | Java | Monitoring | Observability | Partitioning | Python | Scala | Schema management | Stateful stream processing | Stream Joins | Stream processing | Time processing | Windowing | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
Data Engineer | Engineer | Principal | Principal Data Engineer
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