数据管线高级工程师
Tasks
- Build data cleaning labeling quality inspection tools
- Build data visualization capabilities
- Build distributed data processing system
- Build distributed storage and table management
- Collaborate with model teams to deliver data solutions
- Design data models
- Design data pipeline core workflow
- Design high throughput low latency pipelines
- Develop data lake ingest workflow
- Develop data mining toolchain
- Enable data lineage tracking
- Expose data as data services
- Implement data version control
- Implement log tagging and data collection
- Manage data synchronization and data standardization
- Manage memory and I O performance
- Manage metadata and fast search
- Optimize end to end data collection cleaning transformation performance
- Perform offline data processing
- Perform real-time data processing
- Provide unified data access across teams
- Resolve large scale data transmission bottlenecks
- Support algorithm teams with error case localization
- Troubleshoot distributed system performance issues
Perks/Benefits
- N/A
Skills/Tech-stack
Apache Iceberg | Caching | Columnar Storage | Data Lake | Data Lakehouse | Data Lineage | Data Mining | Data Modeling | Data Quality | Data Services | Data Standardization | Data Versioning | Data Visualization | Data cleaning | Data labeling | Distributed Computing | Distributed Systems | Distributed messaging | Docker | ETL | Git | Go | I/O | I/O Optimization | Java | Kafka | Kubernetes | Log Collection | Memory Management | Metadata Management | MongoDB | MySQL | NoSQL | Offline processing | Partitioning | Performance optimization | PostgreSQL | Pulsar | Python | Query engines | RabbitMQ | Real Time | Real-time Processing | Redis | Relational databases | Snapshots | Stream processing | Time processing
Education
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