Aws Developer

Infosys; Bengaluru; On-site; INR 1,200,000 - 2,400,000; Full time

Job summary

Infosys in Bengaluru seeks an experienced Data Engineer to design, implement, and optimize scalable ETL/ELT pipelines on AWS. You will ingest data from diverse sources, transform it, and load into analytical stores to enable BI and analytics across the organization.

The role emphasizes hands-on work with AWS Glue and Redshift, data governance, security controls, and collaboration with analytics teams to deliver reliable, scalable data solutions that empower critical business decisions.

Qualifications

• Design scalable ETL/ELT pipelines on AWS.
• Build data workflows with AWS Glue for reliability and performance.
• Design and manage data warehousing on Redshift with schema design and partitioning.
• Implement data quality checks, governance, and security controls.
• Collaborate with analytics/BI teams to translate requirements into data models.

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. 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.

Skills

AWS

ETL Pipelines

Data Modeling

Data Governance

Tools

AWS Glue

Glue Studio

Amazon Redshift

Data Cataloging

Job description

• Primary skills:Domain->Communication Equipment->Communication Equipment->UAV,Technology->Cloud Platform->AWS Enviornment Provisioning,Technology->Data On Cloud - NoSQL->Amazon Dynamo DB,Technology->Data On Cloud - Platform->AWS
  

• Primary skills:Domain->Communication Equipment->Communication Equipment->UAV,Technology->Cloud Platform->AWS Enviornment Provisioning,Technology->Data On Cloud - NoSQL->Amazon Dynamo DB,Technology->Data On Cloud - Platform->AWS
  

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. 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.