Data Engineer, Selling Partner Insights and Analytics, SPS

Company: Amazon
Location: Bengaluru, Karnataka, IND
Type:
Posted: Sep 6, 2026
Views: 3

✨ AI Summary

Amazon, a global e-commerce leader, is hiring a Data Engineer for its Selling Partner Insights and Analytics team to build the data platform for Paragon, its second-largest Human-in-the-Loop platform. The role focuses on designing scalable data infrastructure and pipelines using native AWS technologies to support reporting, analytics, and LLM/ML models. Candidates should be experienced self-starters with a passion for data-intensive applications and the ability to partner with business owners to shape data architecture. The position is based in Bengaluru, India, and emphasizes high-impact work within a fast-paced, AI-focused environment.

Amazon's Selling Partner Insights and Analytics (SPIA) team is looking for an experienced Data Engineer to help architect and build the data platform that powers Paragon, Amazon's second-largest Human-in-the-Loop platform. Paragon processes over 500 million cases every year and serves 200+ teams and 70,000+ users who handle support and investigation work across Selling Partner Services.

This is a high-impact role for a self-starter who thrives in a fast-paced, ever-changing environment and has a genuine passion for building data-intensive applications. With access to vast datasets and a strong organizational focus on AI/LLM, you will help redefine how data is accessed, trusted, and applied across Selling Partner Services, directly influencing customer experience and operational excellence in the world's largest e-commerce ecosystem.

Key job responsibilities
- Design and operate scalable, cost-effective data infrastructure and pipelines on native AWS technologies, curating data for reporting, analytics, and LLM/ML models.
- Define logical data models and architectures that scale with Paragon's growth into Emerging Marketplaces and worldwide use cases.
- Partner with business owners and technical leaders to gather requirements, shape data architecture, and deliver solutions that meet real business needs.
- Drive Best-At-Amazon (BAA) standards for system efficiency, IMR efficiency, data availability, consistency, and compliance.
- Enable efficient data exploration on large datasets and implement data access controls for stand-alone datasets.
- Build automation that raises the bar on operational excellence, and contribute across the full data engineering lifecycle: design, development, testing, and maintenance.

About the Company

Name: Amazon

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