Walk In | AWS Data Engineer + Pyspark

Tata Consultancy Services; Bengaluru; On-site; INR 2,400,000 - 4,200,000; Full time

Job summary

Tata Consultancy Services (TCS) in Bengaluru invites experienced AWS Data Engineer professionals to join our Walk-In event. You will design, build, and optimize scalable data pipelines on AWS, leveraging Databricks and PySpark to deliver resilient data solutions.

The role demands 6-12 years of hands-on experience with AWS data services, Spark ecosystem, data lakes and data warehousing, and strong scripting and IaC skills. Walk-in date 29-Aug-26, venue at Yeshwanthpur, Bengaluru.

Qualifications

• Hands-on experience with AWS data services (Glue, S3, Lambda, EMR, Redshift, Athena).
• Experience with Spark, PySpark, Hadoop and Databricks.
• Experience building data lakes, data warehouses, and lakehouses.
• Strong ETL/ELT design, data modeling (Star/Snowflake).
• Familiarity with CI/CD, infrastructure-as-code, and Git.
• Knowledge of data governance, security, and compliance.

Responsibilities

• Design, build, and optimize scalable data pipelines on AWS.
• Leverage Databricks and PySpark to enable analytics solutions.
• Ensure adherence to data governance, security, and compliance standards.

Skills

AWS data engineering

Distributed data processing

Data lakes/warehouses

ETL/ELT design

Data governance & security

Tools

Spark

PySpark

Hadoop

Databricks

Terraform

CloudFormation

Git

Job description

Greetings from TCS!!!

Come and join us for an exciting career with TCS!!!

Role- Walk In || AWS Data Engineer + Pyspark

Experience: 6 - 12 Years

Walk In Venue: Tata Consultancy Services

A Block, 2nd floor ,Yeshwanthpur Towers

2GGW+54C, Yeshwanthpur Industrial Suburb, Sattva Knowledge Point

Mahalakshmi Layout,

Bengaluru,

Walk In Date - 29-August-26 (Saturday)

Role Summary

We are seeking an experienced AWS Data Engineer+ Databricks+ Pyspark to design, build, and optimize scalable data pipelines and analytics solutions on AWS. The ideal candidate has strong expertise in cloud-native data services, big data processing, and endtoend data engineering practices.

Required Skills & Qualifications

• Strong experience with AWS services used for data engineering (Glue, S3, Lambda, EMR, Redshift, Athena, Databricks, Kinesis).
• Hands-on experience with distributed data processing frameworks (Spark, PySpark, Hadoop).
• Experience building data lakes, data warehouses, and lakehouse architectures.
• Strong understanding of ETL/ELT design patterns and data modeling (Star/Snowflake).
• Knowledge of CI/CD, infrastructure-as-code (Terraform/CloudFormation), and Git.
• Familiarity with data governance, security, and compliance frameworks