Skills

Nice to have

AWS Certification(s), such as AWS Certified Data Engineer – Associate, AWS Certified Solutions Architect – Associate, or AWS Certified Developer – Associate.
Experience with Infrastructure as Code tools such as Terraform or AWS CloudFormation.
Knowledge of data lake architectures and modern cloud data ecosystems.
Exposure to CI/CD pipelines, automation frameworks, and release management practices.
Experience implementing data governance, data security, and cloud platform best practices.
A passion for building scalable, high-quality data solutions with a mindset focused on continuous learning, innovation, and operational excellence.

About the Role

Design, develop, and maintain scalable data ingestion, transformation, and processing pipelines on AWS.
Build and optimize ETL/ELT workflows using AWS Glue for data integration, cataloging, and processing.
Develop automation, orchestration, and data transformation solutions using Python.
Design and support cloud data warehouse solutions using Amazon Redshift and Snowflake.
Create, manage, and optimize relational database solutions using Amazon RDS.
Develop NoSQL data models and high-performance data applications using Amazon DynamoDB.
Build serverless, event-driven data processing solutions using AWS Lambda.
Ensure data quality, integrity, security, governance, and reliability across cloud data platforms.
Optimize data architectures for scalability, performance, operational resilience, and cost efficiency.
Collaborate with cross-functional stakeholders across Product, Engineering, Analytics, and business teams to understand requirements and deliver business-focused data solutions.
Monitor, troubleshoot, and continuously enhance production data pipelines, workflows, and platforms.
Participate in architecture reviews, code reviews, agile ceremonies, and continuous improvement initiatives.

About You
Minimum Qualifications

Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related technical field.
4–6 years of experience in Data Engineering, Data Integration, or Cloud Data Platform development.
Hands-on experience working with AWS data and analytics services.
Strong expertise in AWS Glue for ETL pipeline development and data catalog management.
Proficiency in Python for data processing, automation, and workflow development.
Experience with Amazon Redshift and/or Snowflake for enterprise data warehousing solutions.
Experience working with relational databases and Amazon RDS.
Knowledge of NoSQL database concepts and hands-on experience with Amazon DynamoDB.
Experience building serverless applications using AWS Lambda.
Strong SQL skills and a solid understanding of data modeling principles.
Experience designing, developing, and supporting large-scale data pipelines in cloud environments.
Familiarity with Agile development methodologies and DevOps practices.
Strong analytical thinking, problem-solving skills, and the ability to work effectively in a collaborative, fast-paced environment.
Excellent communication skills with the ability to engage technical and non-technical stakeholders.

Preferred Qualifications

AWS Certification(s), such as AWS Certified Data Engineer – Associate, AWS Certified Solutions Architect – Associate, or AWS Certified Developer – Associate.

Senior Data Engineer

Compensation

Not disclosed

Location

Chennai, TN

Work setup

Not specified

Seniority

Senior

Employment

Not specified

Experience

4+ years

AWS Certification(s), such as AWS Certified Data Engineer – Associate, AWS Certified Solutions Architect – Associate, or AWS Certified Developer – Associate.
Experience with Infrastructure as Code tools such as Terraform or AWS CloudFormation.
Knowledge of data lake architectures and modern cloud data ecosystems.
Exposure to CI/CD pipelines, automation frameworks, and release management practices.
Experience implementing data governance, data security, and cloud platform best practices.
A passion for building scalable, high-quality data solutions with a mindset focused on continuous learning, innovation, and operational excellence.

About the Role

Design, develop, and maintain scalable data ingestion, transformation, and processing pipelines on AWS.
Build and optimize ETL/ELT workflows using AWS Glue for data integration, cataloging, and processing.
Develop automation, orchestration, and data transformation solutions using Python.
Design and support cloud data warehouse solutions using Amazon Redshift and Snowflake.
Create, manage, and optimize relational database solutions using Amazon RDS.
Develop NoSQL data models and high-performance data applications using Amazon DynamoDB.
Build serverless, event-driven data processing solutions using AWS Lambda.
Ensure data quality, integrity, security, governance, and reliability across cloud data platforms.
Optimize data architectures for scalability, performance, operational resilience, and cost efficiency.
Collaborate with cross-functional stakeholders across Product, Engineering, Analytics, and business teams to understand requirements and deliver business-focused data solutions.
Monitor, troubleshoot, and continuously enhance production data pipelines, workflows, and platforms.
Participate in architecture reviews, code reviews, agile ceremonies, and continuous improvement initiatives.

About You
Minimum Qualifications

Bachelor’s degree in Computer Science, Information Systems, Engineering, or a related technical field.
4–6 years of experience in Data Engineering, Data Integration, or Cloud Data Platform development.
Hands-on experience working with AWS data and analytics services.
Strong expertise in AWS Glue for ETL pipeline development and data catalog management.
Proficiency in Python for data processing, automation, and workflow development.
Experience with Amazon Redshift and/or Snowflake for enterprise data warehousing solutions.
Experience working with relational databases and Amazon RDS.
Knowledge of NoSQL database concepts and hands-on experience with Amazon DynamoDB.
Experience building serverless applications using AWS Lambda.
Strong SQL skills and a solid understanding of data modeling principles.
Experience designing, developing, and supporting large-scale data pipelines in cloud environments.
Familiarity with Agile development methodologies and DevOps practices.
Strong analytical thinking, problem-solving skills, and the ability to work effectively in a collaborative, fast-paced environment.
Excellent communication skills with the ability to engage technical and non-technical stakeholders.

Preferred Qualifications

AWS Certification(s), such as AWS Certified Data Engineer – Associate, AWS Certified Solutions Architect – Associate, or AWS Certified Developer – Associate.