Aws Data Engineer (2 To 5 Years)

Infosys; Hyderabad, Pune District, Chennai District; Hybrid; INR 900,000 - 1,300,000; Full time

Job summary

Infosys is seeking an AWS Data Engineer to design and implement scalable data pipelines on the AWS cloud. You will build and optimize ETL/ELT processes, and develop data integration solutions using services like Glue, S3, Lambda, and Redshift.

You will create and manage data lakes and data warehouses, ensure data quality, and collaborate with analysts, scientists, and stakeholders to meet data-driven goals. 2-5 years of relevant experience is required.

Qualifications

• 2-5 years of experience in building, optimizing, and maintaining scalable data solutions on AWS.
• Hands-on expertise in AWS data services, Python, SQL, ETL development, and big data technologies.

Responsibilities

• Design, develop, and maintain scalable data pipelines on AWS.
• Build and optimize ETL/ELT processes for ingesting and transforming large volumes of data.
• Develop data integration solutions using AWS services such as Glue, S3, Lambda, and Redshift.
• Create and manage data lakes and data warehouses on AWS.
• Optimize data processing workflows for performance, reliability, and cost efficiency.
• Collaborate with data analysts, data scientists, and business stakeholders to understand requirements.
• Implement data quality checks, validation frameworks, and monitoring solutions.
• Troubleshoot and resolve data pipeline and production issues.
• Ensure adherence to data governance, security, and compliance standards.
• Participate in code reviews, testing, deployment, and documentation activities.

Skills

AWS data services

Python

SQL

ETL development

Big data technologies

Tools

AWS Glue

S3

Lambda

Redshift

Job description

Position: AWS Data Engineer
Experience: 2-5 Years
Location: Pan India
Employment Type: Full-Time

Job Summary

We are looking for a talented AWS Data Engineer with 2-5 years of experience in building, optimizing, and maintaining scalable data solutions on the AWS cloud platform. The ideal candidate should have hands‑on expertise in AWS data services, Python, SQL, ETL development, and big data technologies to support enterprise data and analytics initiatives.

Key Responsibilities

• Design, develop, and maintain scalable data pipelines on AWS.
• Build and optimize ETL/ELT processes for ingesting and transforming large volumes of data.
• Develop data integration solutions using AWS services such as Glue, S3, Lambda, and Redshift.
• Create and manage data lakes and data warehouses on AWS.
• Optimize data processing workflows for performance, reliability, and cost efficiency.
• Collaborate with data analysts, data scientists, and business stakeholders to understand requirements.
• Implement data quality checks, validation frameworks, and monitoring solutions.
• Troubleshoot and resolve data pipeline and production issues.
• Ensure adherence to data governance, security, and compliance standards.
• Participate in code reviews, testing, deployment, and documentation activities.