Senior Data Engineer, Price Perception and Evaluation
Amazon.com Services LLC•6h ago
United StatesOnsiteFull-timeSenior Level5+ yrs exp
H-1B verified · 2310 LCAs
Top focus
Data EngineerSenior Data EngineerVp DataData Warehouse Engineer
- Every strikethrough price, reference price
- savings number customers see on Amazon depends on data systems that must be fast, accurate, explainable
- available across the world. This role owns the data foundation behind those experiences. You will design the pipelines, data lakes
- quality mechanisms that help Amazon tell customers when an offer is a good value, power AI shopping experiences with trusted pricing data
- give business leaders a reliable view of how pricing experiences are working at Amazon scale. The scale is rare. Your systems feed shopping detail pages, search, cart, deals, international marketplace launches, finance analysis
- executive reviews across tens of marketplaces and billions of customer impressions a day. The leverage is rarer still. A schema choice, freshness contract
- quality standard you set becomes the way many teams across Pricing build, consume
- reason about reference-price data. We are looking for a senior data-engineering owner who wants to build, not just operate. The next twelve months include modernizing legacy pipelines onto a more flexible platform, creating new customer-impression datasets, improving data discoverability and lineage
- setting the next-generation organizational data architecture for how Pricing teams build and consume reference-price data. You will also help lead the transformation of data engineering in Pricing into the agentic AI era, using AI agents for migration, validation
- operational leverage while keeping human judgment where architecture, data contracts
- quality bars matter most. Key job responsibilities - Design, build
- operate production-grade data pipelines for reference prices, strikethrough prices, savings data
- customer-impression datasets across worldwide marketplaces. - Build solid data lakes that power S-Team, leadership, finance, product
- analytics requests on reference-price topics, with discoverability, lineage
- quality checks designed in so BIEs and analysts can answer questions quickly and reproducibly. - Set the data architecture for how upstream pricing signals are transformed into trusted downstream datasets used by shopping experiences, AI features, executive analytics
- ad-hoc deep dives. - Lead cross-team data contracts across Pricing, Search, shopping detail pages, Deals and Promotions, international marketplaces
- partner teams that consume reference-price data. - Modernize legacy data pipelines onto modern data platforms, including cutover design, validation strategy, backfill planning, operational readiness
- deprecation of redundant datasets. - Raise the operational bar for data freshness, completeness, data-quality monitoring
- incident response across high-scale pricing datasets. - Mentor data engineers and software development engineers on data modeling, pipeline design, migration patterns
- high-quality operational mechanisms. - Lead the transformation of data engineering across the Pricing organization into the agentic AI era. Define when agents should handle rote migration or validation work, how engineers verify those outputs
- how proven patterns become team-wide standards. A day in the life You start the morning deep in a design doc, sketching the schema for a new reference-price dataset and writing the freshness contract that downstream teams will build against. Late morning, you ship a small but high-leverage code review that removes duplicate logic from an existing pipeline. You head out to lunch with the software engineering team. Back at your desk, you kick off an AI agent to migrate a legacy pipeline onto the modern data platform, then settle into a focused block on the harder pieces of the same modernization: the cutover plan is written, validation jobs are running
- the first batch lands for a downstream consumer to sanity-check. You close the day landing a new dataset version that the BIE team will turn into the weekly business-review slide for an SVP read. About the team Price Perception and Evaluation owns the customer-facing pricing experiences that help customers understand value on Amazon, including reference prices, strikethrough prices, savings messages
- the data foundations behind those experiences. We sit at the intersection of pricing, shopping customer experience, data engineering, product
- analytics. Our work has unusually broad reach because the same data foundation serves production shopping surfaces, AI shopping features, business analytics
- leadership inspection. We are a builder-heavy team with a high bar for technical judgment. We value simple architectures, strong ownership, precise data definitions
- mechanisms that make the right thing easy for partner teams. We are also actively changing how data engineering work gets done by using AI agents to accelerate migrations and operations while keeping engineers focused on design, correctness
- long-term maintainability.
- 5+ years of data engineering experience - Experience with data modeling, warehousing and building ETL pipelines - Experience with SQL - Experience in at least one modern scripting or programming language, such as Python, Java, Scala
- NodeJS - Experience mentoring team members on best practices
- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR - Experience operating large data warehouses - Experience operating highly available, distributed systems of data extraction, ingestion
- processing of large data sets
- experience troubleshooting and documenting findings Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability
- other legally protected status. 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.
Required skills
data engineeringdata modelingETLSQLPythonJavaScalaNodeJSHadoopHiveSparkEMR