Data Warehouse Engineer
Tasks
- Build self service data foundation for SQL querying
- Collaborate with report developers to validate data accuracy
- Design, build, and optimize data pipelines
- Develop Gold layer data models for reporting
- Implement data governance security and access control
- Maintain documentation for data models pipelines and workflows
- Onboard new data sources and select ingestion strategy
- Partner with business stakeholders to define business logic
- Profile data to translate stakeholder requirements
- Review and guide work of other data engineers
- Troubleshoot and resolve data pipeline issues
Perks/Benefits
- N/A
Skills/Tech-stack
Access Control | Agile Development | Amazon S3 | Apache Flink | Azure | Azure Data | Azure Data Lake | Azure Data Lake Storage | Cloud Storage | Cloud platform | Data Catalog | Data Governance | Data Lake Storage | Data Modeling | Data Processing | Data Security | Data pipeline | Data pipeline optimization | Databricks | Git | GitHub Copilot | Google Cloud | Google Cloud Platform | Google Cloud Storage | Hadoop | Kafka | LLM | Medallion Architecture | Metadata Management | Microsoft Fabric | Near Real-Time Data Processing | Near-Real-Time data | Near-real-time | Performance Tuning | Pipeline Optimization | PySpark | Python | Query Performance Tuning | Query performance | Real-time Data Processing | SQL | Slowly Changing Dimensions | Star Schema | Synapse | Window Functions
Education
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