Data Engineer, Selling Partner Insights and Analytics, SPS

Amazon; Bengaluru; On-site; INR 900,000 - 1,300,000; Full time

Job summary

Amazon's Selling Partner Insights and Analytics team seeks a Data Engineer to design and operate scalable data infrastructure on native AWS technologies for Paragon, serving 200+ teams and 70,000+ users. You will model data, build ETL pipelines, and enable secure data access across large datasets.

The role emphasizes partnering with stakeholders, delivering data-driven solutions, and driving operational excellence in a fast-paced environment within one of the world's largest e-commerce

Qualifications

• 1+ years of data engineering experience.
• Experience with SQL and data modeling, warehousing, and ETL pipelines.
• Experience with one or more query languages (e.g., SQL, HiveQL, SparkSQL).
• Experience with scripting languages (e.g., Python).
• Bachelor's degree or above in Computer Science, Computer Engineering, Information Management, Information Systems, or related discipline.

Responsibilities

• Design and operate scalable, cost-effective data infrastructure and pipelines on native AWS technologies.
• Define logical data models and architectures for Paragon's growth.
• Partner with business owners to gather requirements and deliver data solutions.
• Drive BA A standards for data availability and compliance.
• Enable data exploration and implement data access controls for datasets.
• Build automation across the data engineering lifecycle.

Skills

SQL

Data modeling

ETL pipelines

Python

SparkSQL

Education

Bachelor's degree in Computer Science or related

Tools

Hadoop

Hive/Spark

AWS (EMR, S3)

Informatica / SSIS

Job description

Data Engineer, Selling Partner Insights and Analytics, SPS

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.

Basic Qualifications

• 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

Preferred Qualifications

• 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 Infrastructure

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