Lead the design and implementation of scalable data pipelines on AWS. You will own the end-to-end lifecycle from ingestion to deployment, ensuring system health through rigorous monitoring and logging.
Responsibilities
- Design and build scalable data pipelines to handle large volumes of diverse data.
- Develop ETL processes using Python and SQL for data cleansing and validation.
- Implement CI/CD pipelines to build artifacts and deploy changes to higher environments.
- Set up monitoring, logging, and alerting mechanisms using AWS CloudWatch.
- Collaborate across technical teams to integrate solutions and ensure delivery.
Required Skills
- 8+ years of experience in data engineering.
- Strong proficiency in Python and SQL.
- Extensive experience with AWS services: Glue, Glue Crawlers, Lambda, Redshift, Athena, S3, EC2, and IAM.
- Hands-on experience with scheduling frameworks like Airflow or AWS Step Functions.
- Proven knowledge of DevOps practices and cloud deployment.
- Bachelor's degree in Computer Science.
Preferred Skills
- Deep expertise in AWS-specific data architecture and pipeline design.