6 days ago
Bengaluru, IndiaMid Level
Responsibilities
- Define data strategy, architecture direction, and the long-term roadmap for the data platform with SDEs.
- Design, build, and operate ETL/ELT pipelines processing billions of customer-interaction and context records per day.
- Manage data migrations, schema and platform updates, pipeline tickets, deployments, and operational support.
- Partner with applied scientists and ML engineers on data contracts, feature pipelines, and data-quality checks for personalization and proactive-agent models.
- Optimize production data delivery, improve scalability, monitor pipeline health, and resolve incidents through root-cause fixes.
- Establish and document best practices for data modeling, warehousing, and pipeline design.
Requirements
- At least 3 years of data engineering experience.
- At least 4 years of SQL experience.
- Experience with data modeling, data warehousing, and building ETL pipelines.
- Preferred experience with AWS technologies including Redshift, S3, AWS Glue, EMR, Kinesis, Kinesis Data Firehose, Lambda, and IAM roles and permissions.
- Preferred experience with non-relational databases and data stores, including object, document, key-value, graph, or column-family databases.
About Amazon
Amazon builds and operates a global e-commerce marketplace, logistics network, and consumer devices, and provides cloud computing via AWS for businesses and developers. The company earns revenue from online retail, third‑party seller services, subscriptions like Prime, advertising, and AWS usage. Founded in 1994 and headquartered in Seattle, it is publicly traded on NASDAQ (AMZN) and serves customers in dozens of countries.