Description

You will build and maintain event-driven data pipelines using AWS services and Python. This role is on-site.

Responsibilities

• Build and maintain event-driven data pipelines using AWS Kinesis, MSK/Kafka, Lambda, Step Functions, SQS/SNS, and Glue/EMR.
• Develop ETL/ELT workflows using Python and PySpark, ensuring performance, scalability, and cost efficiency.
• Design and manage data lake and warehouse structures using S3, Glue Catalog, Athena, and Redshift.
• Implement streaming solutions with checkpointing, stateful transformations, idempotency, and schema evolution.
• Create reusable frameworks, internal libraries, and CI/CD pipelines for automated deployments.

Required Skills

• Strong expertise in Python and PySpark for large-scale data processing.
• Advanced hands-on experience with AWS services including S3, Glue, EMR, Lambda, Step Functions, Kinesis/MSK, DynamoDB, Athena, and Redshift.
• Deep experience building event-driven and streaming data pipelines.
• Strong SQL experience for analytical and ETL workloads.
• Hands-on experience with workflow orchestration tools such as Airflow or Step Functions.
• Experience with CI/CD, Git, and Infrastructure-as-Code (Terraform or CloudFormation).
• 10+ years of working experience.

Preferred Skills

• Experience implementing data security best practices including IAM, encryption (KMS), networking, and governance.
• Ability to lead design reviews, mentor junior engineers, and contribute to engineering best practices.

Key Skills

Education

Any Graduate