Description

You will design and maintain large-scale data pipelines and analytics infrastructure on AWS.

This role is on-site.

Responsibilities

• Build and optimize event-driven and streaming data pipelines using PySpark and AWS services.
• Develop ETL workloads and analytical queries using advanced SQL.
• Implement workflow orchestration and automation with Airflow or AWS Step Functions.
• Manage infrastructure using Terraform or CloudFormation and enforce CI/CD practices.
• Ensure data security, compliance, and cost optimization across cloud environments.

Required Skills

• 10+ years of professional experience in Data Engineering.
• Strong expertise in Python and PySpark for large-scale data processing.
• Advanced hands-on experience with AWS: S3, Glue, EMR, Lambda, Step Functions, Kinesis/MSK, DynamoDB, Athena, Redshift.
• Deep understanding of distributed systems and Spark performance tuning.
• Proficiency in data modeling and SQL for analytical workloads.
• Experience with CI/CD, Git, and Infrastructure-as-Code (Terraform or CloudFormation).
• Knowledge of data security, encryption, networking, and compliance best practices.

Preferred Skills

• Professional experience working with Java.

Key Skills

Education

Any Gradute