AWS Glue Data Engineer

- Designing and building AWS Glue data pipelines to move, transform, and load data across Redshift and cloud data stores
- Developing PySpark jobs for batch and streaming processing, with attention to code readability, performance, and maintainability
- Integrating Kinesis data streams into ingestion workflows for near real-time processing and downstream analytics use cases
- Creating data models and transformation logic that support warehouse development, reporting, and analytical access patterns
- Tuning query performance and pipeline throughput in Redshift, Spark, and related data engineering platforms
- Troubleshooting data integration issues by reviewing source systems, transformation logic, and downstream dependencies
- Collaborating with client stakeholders to gather requirements, clarify data needs, and translate them into technical deliverables
- Reviewing work from junior team members and providing guidance on data pipeline design, development standards, and delivery approach
- Applying cloud engineering and data modernization methods to support scalable data platform implementation and migration activities