Job Description
- Design, build and maintain real-time and batch data pipelines using Python, PySpark, and AWS services.
- Architect and manage cloud infrastructure with a focus on scalability, cost-efficiency, and performance (AWS Glue, Lambda, S3, Athena).
- Implement and optimize ETL/ELT workflows, ensuring data quality and reliability.
- Integrate data from diverse sources, including APIs (REST/GraphQL), into centralized data warehouses.
- Work with streaming technologies like Kafka or Amazon Kinesis to handle high-throughput, low-latency data ingestion.
- Lead data modeling efforts and contribute to the design of enterprise data warehouses and data lakes.
- Collaborate with product, engineering, and analytics teams to identify data needs and translate them into scalable solutions.
- Mentor junior data engineers and contribute to best practices, code reviews, and process improvements.
- Drive innovation by evaluating and implementing emerging t...
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