Description

Join Us in the International Seller Services Central Analytics Team

We are a dedicated group of Engineers within the Seller Services organization at Amazon. Our mission is to deliver data-driven analytical solutions that empower sellers to thrive on Amazon's global platform. We specialize in constructing and maintaining intricate data pipelines that facilitate the seamless integration of data into Amazon's internal tools and teams.

We are currently in search of a brilliant, self-driven, and seasoned Data Engineer/Developer to join our team. In this role, you will have the chance to work on building scalable solutions, including extensive data models and complex ETL pipelines that serve our GenAI ready data layer.

You will be immersed in a substantial business challenge, tasked with creating architecture, designing documents, constructing logical and physical data models, and building intricate ETL pipelines. All of this will be accomplished using a suite of AWS tools such as Lambda, Redshift, S3, DynamoDB, Glue, and Hive. Additionally,



you will be an integral part of a team dedicated to supporting the ISS organization in maintaining and facilitating easy access to our definitive source of metric data.

Key job responsibilities

Construct intricate ETL pipelines utilizing Datanet (Redshift) and Craddle (Spark Sql ).
Create and manage datasets within AWS Dynamo DB, AWS S3, and Amazon Redshift.
Develop complex ETL workflows employing AWS Glue.
Orchestrate step functions through Python / Scala.
Implement and enforce rigorous data quality standards and data governance policies, ensuring data accuracy, consistency, and security. Establish procedures for data validation, cleansing, and lineage tracking.
Continuously monitor and optimize data pipelines and processes to enhance performance and efficiency. Identify bottlenecks and implement enhancements to expedite data processing and minimize latency.
Collaborate closely with data analysts and visualizat

📌 Data Engineer II, International Seller Growth (Hyderabad)
🏢 Amazon
📍 Hyderabad