Data Engineer with GCP
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Summary
Build and optimize GCP-based ETL/ELT pipelines, data models, and scalable architectures to support analytics and AI workloads.
- Analyze bottlenecks
- Automate data processing
- Build ETL/ELT pipelines
- Build pipeline monitoring and alerting
- Build reusable data engineering frameworks
- Create database schemas and data models
- Design data storage strategies
- Design scalable data architectures
- Develop high-performance data pipelines
- Ensure data consistency and traceability
- Establish data governance best practices
- Implement batch and streaming data ingestion
- Improve pipeline throughput and processing efficiency
- Optimize SQL queries
- Optimize database performance
- Support AI and analytics workloads
- Troubleshoot production data issues
- Validate data quality