About this role

Amazon is hiring a mid-level Data Engineer based in Bangalore, India. The posting calls out experience with AWS, Serverless, SQL, Redshift and roughly 3+ years of relevant work.

Role: Data Engineer
Function: data engineering
Level: mid
Track: Individual contributor
Employment: Full-time
Location: Bangalore, India
Experience: 3+ years
Department: Software Development
Posted: Mar 19, 2026

AI Summary

Design and build scalable data pipelines and platforms for AI and analytics applications. Requires 3+ years data engineering experience, 4+ years SQL, and expertise in data modeling, warehousing, and ETL pipelines. AWS technologies and non-relational databases preferred.

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Job description

from Amazon careers

We are looking for a Data Engineer to help build and scale the data foundation powering next-generation AI and analytics. The role focuses on designing robust, scalable data pipelines and platforms that enable high-quality datasets for advanced AI applications. You will work on modern data architectures, ensuring performance, reliability, and efficient data processing at scale. The position offers opportunities to experiment with emerging AI-driven data techniques and intelligent data systems. You will collaborate with scientists, analysts, and platform teams to translate complex data needs into well-designed engineering solutions. A strong focus will be placed on data quality, automation, and platform innovation. The ideal candidate enjoys solving complex design challenges and building systems that scale seamlessly. Join us to shape the data backbone that accelerates AI innovation

Basic Qualifications

- 3+ years of data engineering experience
- 4+ years of SQL experience
- Experience with data modeling, warehousing and building ETL pipelines

Preferred Qualifications

- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)

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