Insights into Company Bills & Payments

About Amazon

Outlets operated by Amazon.

All openings at AmazonMore Food & Beverages companies Original posting ↗

Requirements and qualifications

The complete company-provided qualifications are included in the job profile below and confirmed on the official application page.

What you will get

Benefits, compensation and workplace terms vary by location and are shown exactly as provided by Amazon on its official application page.

Amazon

Data Engineer, Selling Partner Insights and Analytics, SPS

📍 IN, KA, Bengaluru, 💼 1–+ years🏠 ◷ full-time

About the role

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 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. - 1+ years of data engineering experience- Experience with SQL- 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)- Bachelor's degree or above in Computer Science, Computer Engineering, Information Management, Information Systems, or other related discipline - Experience with big data technologies such as: Hadoop, Hive, Spark, EMR- Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.- Knowledge of AWS InfrastructureOur inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Job seeker reviews of Amazon

First-party reviews shared by people using Ascendia. We do not copy reviews from other job portals.

★★★★★ New 0 reviews
No reviews have been published yet. Be the first job seeker to share a genuine experience.

Have experience with this company?

Sign in as a student or job seeker to write a review.

Sign in to review

Similar roles based on your skills

Prepared from active Ascendia jobs using skills, department, engineering discipline, location and work mode.