SP-AI Data Products is a small, high-autonomy team that builds the data infrastructure powering AI-driven commerce for millions of Amazon Selling Partners worldwide. Our mission is straightforward: make every AI agent interaction measurable, governable, and improvable through trusted, self-service data products. We exist so that product teams can ship with confidence, risk teams can detect abuse in real time, scientists can train better models, and leadership can see exactly how the business is performing without waiting for someone to compile a report.
We're a team of software engineers, data engineers, and business intelligence engineers split between Bengaluru and Seattle. We operate like a startup inside Amazon: small enough that every person's work is visible and consequential, but connected to a business growing at 7x year-over-year that serves 50+ domain teams, thousands third-party developers, and millions of sellers. Our customers are internal: the engineering teams building AI agents, the risk and trust teams protecting the ecosystem, the product managers tracking adoption, and the scientists improving model quality.
We build for all of them simultaneously through governed, tenantized data products rather than one-off reports.
Our culture is built on ownership and craft. We write production-grade code in Java, Scala, and Python. We design schemas that dozens of teams consume. We hold each other to high engineering standards through rigorous code and design reviews, and we invest in mentorship because raising the bar across the team matters more than any individual contribution. We're transparent about what we are: a lean team executing an ambitious transformation from reactive reporting into a production data product organization built entirely on AWS.
If you want to work somewhere your architectural decisions directly shape how an organization operates, where you'll have real autonomy to drive outcomes, and where the problems are genuinely hard and unsolved, this is the team.
- 7+ years of data engineering experience
- 5+ years of development/programming/scripting language (Python/Java/Bash/Perl) experience
- Experience with AWS services including S3, Redshift, Sagemaker, EMR, Kinesis, Lambda, and EC2
- Experience with data modeling, warehousing and building ETL pipelines
- Experience leading engineering teams as a mentor or tech lead, or experience leading the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems
- Experience in any Bigdata architecture, or experience managing full application stacks from the OS up through custom applications and experience with automation and any version control tools
- Experience in Kafka, or experience in any Bigdata architecture and experience in Redshift
- Experience in data warehouse technical architectures, data modeling, infrastructure components, ETL/ ELT and reporting/analytic tools and environments, data structures and hands-on SQL coding
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.
