Description

Build and maintain scalable data pipelines on AWS using Glue, PySpark, and Redshift.

This role is hybrid.

Responsibilities

• Develop and maintain data pipelines on AWS using AWS Glue and PySpark.
• Build and optimize data models and transformations for analytics in Amazon Redshift.
• Implement scalable batch data processing jobs and data ingestion workflows.
• Write and tune SQL for data extraction, validation, and analytics enablement.
• Collaborate with analytics and engineering teams to deliver production-ready datasets.

Required Skills

• 5-8 years of experience in Data Engineering.
• Strong hands-on experience with AWS services.
• Experience with AWS Glue for data integration and ETL.
• Strong knowledge of PySpark and distributed data processing.
• Hands-on experience with Amazon Redshift.
• Strong SQL skills for data extraction, transformation, and validation.
• Experience building and maintaining scalable data pipelines.
• Good understanding of data modeling and data warehousing.

Preferred Skills

• Experience with Databricks.
• Knowledge of AWS data services such as S3, Lambda, and EMR.
• Experience with data analytics and production data pipelines.

Key Skills

Education

Any Graduate