Senior AWS Engineer

Overview

Support the design, implementation, testing and optimization of data ingestion, transformation and analytics capabilities across the ADC platform, building reliable, scalable pipelines on AWS-native data services.

What you'll do

• Develop, configure and support data ingestion workflows using AWS Glue, Glue Crawlers, AWS Lambda, Amazon S3, Amazon EventBridge and Amazon Redshift Serverless.
• Execute ingestion testing and validate data movement across raw, curated and consumption layers.
• Monitor and support schema discovery, schema inference and schema drift resolution.
• Troubleshoot and resolve pipeline issues, event sequencing failures and ingestion bottlenecks.
• Collaborate with senior engineers to maintain stable data flows across Development and UAT environments.
• Implement and maintain data models within Amazon Redshift to support reporting, analytics and NLP-driven query capabilities.
• Optimize Redshift COPY operations, data loading strategies, partitioning and performance tuning.
• Support normalization, transformation and enrichment to improve data consistency and usability.
• Ensure datasets are query-ready for downstream business intelligence and AI-driven consumption.
• Maintain metadata integrity through AWS Glue Data Catalog and support governance processes using AWS Lake Formation.
• Implement and enhance data quality validation checks and reconciliation mechanisms.
• Ensure adherence to data governance, security and access control standards.
• Monitor and improve data lineage, catalog accuracy and data discoverability.
• Support implementation and configuration of Amazon QuickSight for self-service analytics and NLP-based querying.
• Collaborate with Platform and DevOps teams on QuickSight setup, dataset modeling, security integration and NLP feature enablement.
• Ensure analytics datasets are optimized for performance, accuracy and business consumption.
• Analyze application and pipeline behavior using Amazon CloudWatch Logs and monitoring tools.
• Support incident analysis, root cause investigations and performance improvement initiatives.
• Contribute to operational documentation, runbooks, deployment procedures and support guides.
• Promote reproducibility, automation and engineering best practices across the data platform.

What you'll need

• Mandatory: AWS.
• Hands-on experience with AWS data engineering services.
• Strong data modeling expertise.
• Solid understanding of distributed data processing patterns.

Details

• Location: Bengaluru.