AWS Data Engineer

You will be a key contributor in designing and building robust, scalable data solutions on AWS that power analytics, reporting, and data-driven decision making. In this role, you will work with modern cloud-native services to create secure, high-performing data pipelines and warehouses that serve multiple business teams. With your experience, you’ll help shape best practices for data engineering, optimize performance, and ensure data reliability across the organization.

You’ll collaborate closely with data analysts, data scientists, and product teams to understand their needs and translate them into efficient data models and ETL/ELT workflows. This is an opportunity to take ownership, influence architecture decisions, and continuously improve our data ecosystem while working in a collaborative, learning-focused environment.

Responsibilities

Design, develop, and maintain scalable ETL/ELT data pipelines on AWS to ingest, transform, and load data from diverse sources.

Build and optimize data workflows using AWS Glue, ensuring reliability, reusability, and performance of jobs and crawlers.

Design, implement, and manage data warehousing solutions on AWS Redshift, including schema design, partitioning, and performance tuning.

Implement data quality checks, validation rules, and monitoring to ensure accuracy, completeness, and consistency of data assets.

Collaborate with analytics and business teams to understand reporting and BI requirements and translate them into efficient data models and datasets.

Apply best practices for security, compliance, and governance across AWS data services, including access control and encryption standards.

Troubleshoot and resolve data pipeline issues, optimize job performance, and proactively improve system reliability and scalability.

Contribute to documentation, standards, and reusable frameworks for data engineering on AWS to support team-wide efficiency and consistency.

Technical requirements

Deep hands-on experience with AWS Glue, including job orchestration, Glue Studio/Jobs, and integration with other AWS data services.

Strong experience with AWS Redshift, including cluster management, query optimization, workload management, and cost/performance tuning.

Demonstrated track record of delivering end-to-end data engineering solutions on AWS for analytics, BI, or data science use cases.

Experience implementing data governance, metadata management, and data cataloging using AWS-native or similar tools.

AWS-related certification (e.g., AWS Certified Data Analytics, AWS Certified Solutions Architect, or AWS Certified Developer) is a strong plus.

Ability to work in cross-functional teams, communicate technical concepts clearly, and mentor junior engineers on AWS data best practices.

Additional responsibilities

Infosys is a global leader in next-generation digital services and consulting. We enable clients in more than 50 countries to navigate their digital transformation. With over four decades of experience in managing the systems and workings of global enterprises, we expertly steer our clients through their digital journey. We do it by enabling the enterprise with an AI-powered core that helps prioritize the execution of change. We also empower the business with agile digital at scale to deliver unprecedented levels of performance and customer delight. Our always-on learning agenda drives their continuous improvement through building and transferring digital skills, expertise, and ideas from our innovation ecosystem.

Infosys provides equal employment opportunities to applicants and employees without regard to race, color, sex, gender identity; sexual orientation, religious practices and observances; national origin; pregnancy, childbirth, or related medical conditions; status as a protected veteran or spouse/family member of a protected veteran; or disability.

Education

Bachelor of Engineering