In this role, you will serve as the primary guardian of our data ecosystem, ensuring the seamless operation, reliability, and performance of complex data pipelines.

You will work closely with cross-functional engineering teams, data architects, and business stakeholders to troubleshoot critical issues, optimize existing ETL workflows, and maintain high availability for data-driven decision-making.

Your contribution will directly impact the stability of our production environment, ensuring that our customers receive accurate, timely data insights that drive business growth and operational efficiency.

Key Responsibilities :

- Monitor and maintain production data pipelines to ensure 99.9% uptime and data integrity for internal business units.

- Troubleshoot and resolve complex data discrepancies and performance bottlenecks within AWS-based ETL processes to minimize downtime and improve system efficiency.

- Collaborate with software engineering teams to perform root cause analysis on recurring production incidents, implementing long-term fixes that prevent future system failures.

- Optimize SQL queries and database performance to ensure rapid data retrieval and reporting for stakeholders across the organization.

- Manage AWS infrastructure components, including S3, Glue, and Redshift, to ensure cost-effective and scalable data storage and processing solutions.

Required Skillset :

- Demonstrated expertise in managing and supporting large-scale data pipelines within the AWS ecosystem, with a deep understanding of cloud-native data architecture.

- Advanced proficiency in writing and optimizing complex SQL queries to handle high-volume data sets and resolve performance-related production issues.

- Proven ability to design, debug, and maintain robust ETL workflows, ensuring data consistency and accuracy across multiple environments.

- Strong analytical mindset with the ability to communicate technical constraints and solutions clearly to non-technical stakeholders and cross-functional team members.

- Exceptional problem-solving skills, capable of working independently in a fast-paced environment while maintaining high standards of documentation and process compliance.

- A Bachelor's degree in Computer Science, Information Technology, or a related quantitative field, combined with 4 to 6 years of relevant experience in a production support or data engineering capacity.

- Flexibility to operate effectively in a hybrid work environment, coordinating seamlessly with distributed teams across Chennai, Hyderabad, and Bangalore.