Description

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.

Key Skills

Education

Bachelor's degree in Computer Science