AWS Sr Data Engineer (Spark/EMR/Glue/Iceberg)

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

Job summary

Tata Consultancy Services is seeking an AWS Senior Data Engineer (Spark/EMR/Glue/Iceberg) in All India with 6-12 years of experience. You will design and implement data pipelines on AWS data lake architectures.

The role emphasizes scalable ETL/ELT development, integrating data from multiple sources into AWS analytics platforms, and ensuring data quality, governance and security. Candidates should have hands-on expertise with EMR, Glue, Spark, Iceberg, S3, Athena, Lambda, Redshift, Python and

Qualifications

• Hands-on experience with AWS EMR, Glue, Spark and Iceberg.
• Strong Python and SQL skills for data processing and analytics.
• Experience with large-scale Data Lake implementations and data governance.

Responsibilities

• Design and develop scalable data pipelines using Spark, EMR, and Glue.
• Build and manage Data Lake solutions with Apache Iceberg on AWS.
• Optimize ETL/ELT workflows for performance and reliability.
• Integrate data from multiple sources into AWS analytics platforms.
• Implement data quality, governance, and security best practices.

Skills

Python

SQL

Data modeling

Airflow

CI/CD & DevOps

Tools

AWS EMR

AWS Glue

Apache Spark

Apache Iceberg

Amazon S3

Athena

Redshift

AWS Lambda

Job description

Role & responsibilities

Hiring: AWS Sr Data Engineer (Spark/EMR/Glue/Iceberg)

Location: All India

Experience: 6-12 Years

Employment Type: Full-Time

Preferred candidate profile

Key Skills

• AWS EMR
• AWS Glue
• Apache Spark (PySpark/Scala)
• Apache Iceberg
• Amazon S3
• Data Lake Architecture
• ETL/ELT Development
• AWS Lambda
• Athena
• Redshift
• Python
• SQL
• Airflow
• CI/CD & DevOps

Responsibilities

• Design and develop scalable data pipelines using Spark, EMR, and Glue.
• Build and manage Data Lake solutions with Apache Iceberg on AWS.
• Optimize ETL/ELT workflows for performance and reliability.
• Integrate data from multiple sources into AWS analytics platforms.
• Implement data quality, governance, and security best practices.
• Collaborate with architects, analysts, and business stakeholders.

Requirements

• Strong hands-on experience with AWS EMR, Glue, Spark, and Iceberg.
• Proficiency in Python and SQL.
• Experience with large-scale data processing and Data Lake implementations.
• Knowledge of AWS services including S3, Athena, Lambda, and Redshift.
• Understanding of data modeling, partitioning, and performance tuning.

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