Description

You will design, build, and maintain scalable ETL and data processing pipelines for enterprise data platforms.

This role is on-site.

Responsibilities

• Build production-grade data pipelines using Python, PySpark, and AWS Glue.
• Develop cloud-native solutions leveraging S3, Lambda, Step Functions, ECS, SNS, and SQS.
• Optimize Spark jobs, SQL queries, and data workflows for performance and scalability.
• Maintain PL/SQL scripts and database solutions in Oracle, PostgreSQL, or similar RDBMS.
• Implement CI/CD, automated testing, version control, and monitor production environments.

Required Skills

• 5+ years of hands-on experience building data pipelines with Python and PySpark.
• Expertise with AWS services: S3, Glue, Lambda, Step Functions, ECS, SNS, SQS.
• Strong SQL and PL/SQL development experience with Oracle or PostgreSQL.
• Experience with Spark performance tuning and large-scale data processing.
• Solid understanding of software development best practices including Git and CI/CD.
• Experience with monitoring, observability, alerting, and production support processes.
• Bachelor's degree in a relevant field.

Preferred Skills

• Familiarity with Infrastructure-as-Code tools and DevOps practices.
• Knowledge of data governance, security, and compliance standards.
• Experience working in Agile/Scrum environments.

Key Skills

Education

Bachelor's degree