# Data Engineer, Amazon Live Data Engineering, Sciences and Analytics (DESA) at Amazon

Amazon is hiring a Data Engineer, Amazon Live Data Engineering, Sciences and Analytics (DESA) in Seattle, United States. It pays $132k-$179k a year and Level rates it Works on AI ●●●○; you can [apply on Level](https://jobsbylevel.com/go/fd93feea-01a3-4f94-8705-3de50b002678?utm_medium=ai-agent).

AI Level 3, AI centrality 66 out of 100. US, WA, Seattle.

## Details

- Company: [Amazon](https://jobsbylevel.com/companies/amazon)
- AI level: AI Level 3 (score 66 out of 100)
- Location: US, WA, Seattle
- Salary: $132k-$179k
- Posted: October 19, 2026
- Apply: https://jobsbylevel.com/go/fd93feea-01a3-4f94-8705-3de50b002678?utm_medium=ai-agent

## Description

Description Amazon Live is building the future of shoppable video — connecting brands with customers through livestreams, short-form video, and creator-driven content across Amazon Shopping, Fire TV, Prime Video, and social platforms. The product serves millions of monthly viewers, processes billions of events daily across 9 marketplaces, and generates tens of millions of dollars in advertiser revenue, with a goal to reach 100MM+ MAUs and 20K+ brands in the next couple of years. Amazon Live has a mature, high-performing data platform powering reporting across 9 marketplaces, 14+ dashboards, real-time creator analytics, and a growing suite of AI-native tooling (self-serve analytics agents, agentic operational assistants). The opportunity ahead is to build the next layer on that strong foundation: the team is standing up an intelligence layer — causal measurement, content intelligence, and ranking signals — and that requires a new class of foundational, reusable data assets purpose-built for both analytics and ML consumption. This role builds them. We are looking for a Data Engineer to join the DESA team as a dedicated owner of forward-looking data architecture. You will design and build durable, well-modeled datasets that serve three consumers at once: the BIE for executive reporting, the Applied Scientists for model training, and downstream ML systems (ranking, personalization, recommendations) for feature consumption. The goal is leverage — build an asset once, serve many use cases, and let the whole team move faster on top of it. Your work becomes the foundation the science function builds on: when the data assets are ready ahead of need, scientists model from day one instead of waiting on bespoke pipelines. This is a high-ownership role on a team that moves fast. You will go from problem to production quickly, in a challenging and fast-paced environment, and you will work across the full breadth of the data domain — platform engineering, data modeling, ML-ready feature production, data quality, and AI-assisted development. You will partner closely with Applied Scientists, MLEs, fellow Data Engineers, and the BIE, giving you the opportunity to learn and execute across every aspect of a modern data organization — from raw event ingestion through the models and reporting that move multi-million-dollar business decisions. Key job responsibilities - Design and build a content metadata layer that unifies broadcast events, product catalog data, creator profiles, and show metadata into reusable assets consumed by both dashboards and models. - Build cross-session shopper profile datasets that sessionize event data across visits and compute rolling engagement metrics (frequency, recency, depth, conversion lag). - Build integration pipelines connecting retail catalog and advertising performance data into the Amazon Live platform, unlocking new dimensions for analytics and ML. - Produce structured, ML-ready datasets that feed Applied Scientists' models and serve features to downstream ranking and personalization systems. - Own and advance data quality: proactive monitoring and anomaly detection so the team stays ahead of issues. - Advance platform engineering maturity — CI/CD for ETL (BDT/Maestro), standardized deployment, and AI-assisted code generation and review. - Partner with Applied Scientists, MLEs, DEs, and the BIE to align data assets to model, serving, and reporting needs. A day in the life You will move fast across a broad surface. Some weeks you will be designing a denormalized content metadata asset with an Applied Scientist to unblock a new model; other weeks you will be integrating a retail or advertising data source, hardening a pipeline's CI/CD, building data-quality alarms, or packaging features for the distribution team's ranking systems. You will partner daily with scientists, MLEs, DEs, and the BIE — scoping what to build and how it will be consumed — and you will have self-serve analytics agents and agentic

The description is cut here. Read the full offer: https://jobsbylevel.com/jobs/data-engineer-amazon-live-data-engineering-sciences-and-analytics-desa-at-amazon-06d03a

Source: https://jobsbylevel.com/jobs/data-engineer-amazon-live-data-engineering-sciences-and-analytics-desa-at-amazon-06d03a

## Cite this page

Level. https://jobsbylevel.com/jobs/data-engineer-amazon-live-data-engineering-sciences-and-analytics-desa-at-amazon-06d03a.

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