Amazon

Data Engineer I

Posted On

Sept. 14, 2025

Location

Bengaluru, Karnataka

Experience Level

Freshers/Experienced

Job Type

Data Science

Apply By

Dec. 23, 2025

Job Description

Fulfillment by Amazon (FBA) enables sellers to scale their businesses globally by leveraging Amazon’s world-class fulfillment network. Sellers using FBA benefit from fast, reliable shipping, Prime delivery eligibility, and hassle-free returns—allowing them to focus on growth while we handle operations. The WW FBA Central Analytics team builds and operates scalable, enterprise-grade data infrastructure, tools, and analytics solutions that power WW FBA business. We partner across global product, program, and operations teams to unify diverse datasets, deliver self-service analytics, and develop next-generation capabilities using LLMs to unlock insights.

Our charter includes building the foundational pipelines, governance frameworks, and intelligent interfaces that enable internal customers to query, analyze, and act on complex datasets with natural language. This is an opportunity to work on one of the largest, complex, and critical analytics ecosystems, designing solutions that combine massive scale, high reliability, and advanced AI.

We are seeking a Data Engineer I who will support a GenAI-powered insights assistant initiative by building and scaling ingestion and embedding pipelines for unstructured WW FBA knowledge bases. Your role ensures the retrieval-augmented generation system accesses fresh, relevant document embeddings to enhance AI-driven insights and user query satisfaction.

Key job responsibilities
- Build batch and streaming data pipelines using Spark and AWS streaming services.
- Implement automated checks to ensure data consistency across different data types.
- Define and maintain data contracts with source teams to keep schemas consistent.
- Develop cross-domain metadata services linking structured and unstructured data catalogs.
- Create APIs and event-driven workflows integrating AI insights with business tools.
- Monitor pipeline health, costs, and SLA adherence.- 1+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
- Experience with one or more scripting language (e.g., Python, KornShell)

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