AWS Data Engineer | 5 to 10 years | One of the leading Big4

Job Title: AWS Data Engineer

Experience: 5 to 10 Years

Budget: 25 to 32 LPA

Location: Bangalore

Type: Full-Time

Primary Skills: AWS Glue , Lamda , Redshift , Python , Pyspark , Sql

Were looking for an AWS Data Engineer who has strong, hands-on experience with AWS Glue, Lambda, Redshift, Python, PySpark, and SQL . This role will focus on building and maintaining data pipelines in AWS and helping us improve how data flows through our systems.

What youll be working on

• Building and maintaining ETL/ELT pipelines using AWS Glue and PySpark .
• Writing Lambda functions in Python for automation and event-driven workflows.
• Working with Redshift for data warehousing, including query optimization and data modeling.
• Writing and tuning SQL for transformations, reporting, and general data processing.
• Setting up and managing data movement across S3, Glue Catalog, Redshift, and other AWS services.
• Troubleshooting issues in data jobs and improving overall performance and reliability.
• Collaborating with analysts, data scientists, and cross-functional teams to support data needs.

What were looking for

• Strong hands-on experience with AWS Glue and PySpark .
• Good working knowledge of AWS Lambda and Python-based automation.
• Experience with Redshift (including performance tuning, distribution keys, sort keys, etc.).
• Solid SQL skills and experience working with large datasets.
• Familiarity with data modeling, ETL processes, and general data engineering best practices.
• Ability to work independently and take ownership of end-to-end data workflows.
• Strong problem-solving skills and willingness to dive deep into data issues.

Nice to have

• Experience with AWS Step Functions or other orchestration tools.
• Exposure to CI/CD practices, version control, and basic DevOps workflows.
• Knowledge of data quality frameworks or monitoring tools.
• Experience with Glue Studio, Redshift Spectrum, or Athena.