Data Engineer, Selling Partner Insights and Analytics, SPS

Amazon is hiring a Data Engineer, Selling Partner Insights and Analytics, SPS in Bengaluru, India. Level rates it ; you can apply on Amazon.

Level's read on this job

Level rates this data engineer role Works on AI ●●●○: the daily work is on AI products, without building the model.
Tools and skills the posting cites include SQL, Python and Spark.
Level classifies it as a mid-level role.
Level lists 20,000+ other open roles at Amazon.

AI in this role

Build and operate scalable data pipelines and infrastructure supporting human-in-the-loop and LLM/ML platforms.

SQLPythonSparkHadoopAWS

etldata-modelingdata-warehousingpipelines

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

Our 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.

How we rate this

Data Engineer, Selling Partner Insights and Analytics, SPS at Amazon rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Data Engineer, Selling Partner Insights and Analytics, SPS is an open job at Amazon.
Level rates this role AI Level 3 of 4: Works on AI.
The role is based in IN, KA, Bengaluru.
The job was posted on September 6, 2026.
Seniority: mid.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

ETLData ModelingData WarehousingPipelinesSQLPythonSparkHadoop

Also common in data engineer jobs at this level

Databricks Machine learning Azure Airflow Generative AI Snowflake

Pay

Typical data engineer job: $146k

This posting doesn't list pay. Use the typical data engineer figure when pay comes up. See data engineer jobs

Questions you could be asked

Tell me about a project where etl was part of your work. What did you do?
Tell me about a project where data modeling was part of your work. What did you do?
Tell me about a project where data warehousing was part of your work. What did you do?
Tell me about a project where pipelines was part of your work. What did you do?
Walk me through how you've used SQL in your day-to-day work.

Adapt your resume

List these exact terms on your resume: ETL, Data Modeling, Data Warehousing, Pipelines, and SQL. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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