Description

You will design, develop, and maintain scalable data pipelines and ETL workflows on AWS, handling large-scale structured and unstructured data across cloud and on-premise environments.

This role is on-site.

Responsibilities

• Build and optimize data pipelines using PySpark, AWS Glue, and EMR for performance and cost-efficiency.
• Develop serverless data processing solutions using AWS Lambda, Step Functions, and Athena.
• Manage infrastructure as code with CloudFormation and deploy via CI/CD pipelines using Jenkins.
• Collaborate with stakeholders to translate business requirements into reliable, scalable data solutions.

Required Skills

• 5+ years of experience with Python and SQL for data engineering tasks.
• Proficiency in PySpark and ETL tools like Informatica.
• Hands-on experience with AWS data services: S3, Glue, EMR, Lambda, Step Functions, Athena.
• Database experience with Oracle, SQL Server, and PostgreSQL.
• Familiarity with infrastructure and operations tools: Jenkins, ServiceNow, Jira, Confluence.

Preferred Skills

• Experience with Java or Scala programming.
• Knowledge of AWS Bedrock, Kinesis Datastream, or Snowflake.

Key Skills

Education

Bachelor's degree