Amazon

Data Engineer II, Flex Analytics

Posted On

Aug. 1, 2025

Location

Bengaluru, Karnataka

Experience Level

Freshers/Experienced

Job Type

Business Intelligence

Apply By

Aug. 19, 2025

Job Description

Interested in the gig economy? Come be a part of it. The Amazon Flex Analytics Team is building a data platform that powers Amazon Flex worldwide. We’re working hard, having fun, and making history!

We are looking for candidates who want to help shape the future of Flex. Specifically, we are looking for a Data Engineer who is passionate about data architecture and wants help us use data to understand Flex Driver behavior and satisfaction. In this role, you will develop and support the data technologies that give our teams flexible and structured access to their data, including implementation of a self-service analytics platform, defining metrics and KPIs, and automating reporting and data visualization.

The successful candidate considers themselves an enterprise data architect. You should excel in the design, creation, and management of analytical data infrastructure. You will be responsible for designing and implementing scalable processes to publish data and build solutions to reconcile data for integrity and accuracy of data sets used for analysis and reporting. You should have broad understanding of RDBMS, ETL, Data Integration, Data Warehousing, Data Governance and Data Lakes. Experience with Python, R, or Spark is highly preferred and will put you at the top of the list.

Key job responsibilities
Develop and improve the current data architecture using AWS Redshift, AWS S3, Spark and EMR.

Improve upon the data ingestion models, ETL jobs, and alarming to maintain data integrity and data availability.

Stay up-to-date with advances in data persistence and big data technologies and run pilots to design the data architecture to scale for increasing data volumes.

Partner with BIEs and Analysts across teams such as product management, operations, finance, marketing and engineering to build and verify hypothesis to improve the business performance.- 3+ years of data engineering experience
- 4+ years of SQL experience
- Experience with data modeling, warehousing and building ETL pipelines

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