AWS Lead Data Engineer

Infosys; Chennai District; On-site; INR 900,000 - 1,500,000; Full time

Job summary

Infosys is seeking an experienced Data Engineer in Chennai to design and maintain scalable data pipelines using AWS Glue, Lambda, and Step Functions. You will build data ingestion for S3-based data lakes, implement ETL/ELT workflows, and apply data governance with Lake Formation and IAM.

You will collaborate with cross-functional teams in an Agile environment and mentor junior engineers. Responsibilities include optimizing performance, ensuring reliability and security, and providing production

Qualifications

• IT experience with strong Data Engineering background.
• Hands-on AWS data services and data lake architecture.
• Experience in Agile delivery environments.

Responsibilities

• Develop and maintain scalable data pipelines on AWS.
• Build and optimize ETL/ELT workflows for structured data.
• Mentor junior engineers and provide technical guidance.

Skills

Python

SQL

ETL

Data Warehousing

Data Modeling

Agile

Tools

AWS Glue

AWS Lambda

AWS Step Functions

Amazon S3

Lake Formation

IAM

ECS

Job description

Job Description:

IT experience with strong Data Engineering background. Hands-on expertise in AWS Glue, Lambda, Step Functions, S3, and Lake Formation. Strong programming experience in Python and SQL. Experience building enterprise-scale Data Lake solutions. Good understanding of IAM roles, policies, and AWS security best practices. Experience with container technologies and ECS. Strong knowledge of ETL, Data Warehousing, and Data Modeling concepts. Experience working in Agile delivery environments.

Develop and maintain scalable data pipelines using AWS Glue, Lambda, and Step Functions. Build and optimize data ingestion frameworks on Amazon S3-based data lakes. Design and implement complex ETL/ELT workflows for structured and unstructured data. Develop reusable components and automation frameworks for data processing. Implement data governance and access control using Lake Formation and IAM. Deploy and manage containerized workloads on ECS. Optimize data processing performance, reliability, and scalability. Perform troubleshooting, root cause analysis, and production support activities. Collaborate with cross-functional teams to deliver business-driven data solutions. Mentor junior engineers and provide technical guidance to project teams.