Data Engineer, Amazon Ads

Amazon

SEATTLE, WA

JOB DETAILS
SKILLS
Advertising, Amazon Simple Storage Service (S3), Apache Hadoop, Apache Hive, Apache Spark, Artificial Intelligence (AI), Automation, Best Practices, Big Data, Code Reviews, Data Management, Data Modeling, Data Quality, Data Sets, Data Warehousing, Database Extract Transform and Load (ETL), Dimensional Modeling, Ecosystems, Electronic Medical Records, Engineering, Finance, Financial Management, Java, Machine Tool, Mentoring, Node.js, Productivity Management, Python Programming/Scripting Language, Reporting Dashboards, SPICE (Simulation Program with Integrated Circuit Emphasis), SQL (Structured Query Language), Scala Programming Language, Scripting (Scripting Languages), Service Level Agreement (SLA), Startup, Team Building, Technical Leadership, Telemetry
LOCATION
SEATTLE, WA
POSTED
30+ days ago
Description This is a ground-up, greenfield build - Finance for one of Amazon Ads' newest bets in the agentic space. No legacy pipelines, no inherited dashboards, no pattern to follow. If you're energized by shaping data infrastructure from zero to one inside a fast-moving org, keep reading. What we're building: - A finance data platform powering the FAIM org (Full-Funnel Agentic Intelligence & Models) - the team building the next generation of agentic AI advertising products - Pipelines and models that turn raw data into decisions for greenfield products - Self-service reporting that scales spanning Engineering, Science, PM-T, and Design across multiple AI native advertising products This is a startup team within Amazon Ads Finance with an ambitious vision and the runway to build it right the first time. We're looking for a senior Data Engineer who brings: - Deep SQL fluency and 5+ years architecting and operating production ETL on Redshift, Andes, or equivalent at scale - Hands-on depth with the Amazon data stack - Datanet/ETLM, Cradle, Andes 3.0, Redshift Spectrum, EDX, and QuickSight (SPICE) - Strong dimensional data modeling judgment - fact/dim design, SCDs, and the experience to make the right denormalization, partitioning, and lifecycle calls without supervision - Python (or equivalent) for orchestration, data quality automation, and pipeline tooling beyond SQL - A willingness to set the bar - define data quality, lineage, SLA, and reliability standards for the org and hold the line on them - The ability to operate in ambiguity - turn open-ended finance and program questions into durable data products with minimal scoping help - Excitement about leading the data partnership with Finance Managers, PM-Ts, Scientists, and Engineering, and mentoring more junior engineers as the team grows - AI-native experience for automation and defect/opportunity identification using tools such as Kiro, Claude Code, or equivalent Key job responsibilities - Own it end-to-end - set the technical direction for the FAIM data warehouse, ETL pipelines, and reporting layer - Build the tools - architect and operate Datanet/ETLM jobs, Cradle profiles, Andes datasets, and dashboards that finance partners trust as source of truth - Land the data - integrate telemetry from across Amazon's data ecosystem (Andes subscriptions, EDX, S3, internal services) into a clean, query-ready layer - Move fast - deliver on OP1/OP2 cycles, MBR/QBR rhythms, and ad-hoc executive asks with bias for action - Simplify complexity - turn messy, multi-source data into well-documented dimensional models that scale with the org - Raise the bar - drive code and design reviews and set data quality and pipeline reliability standards Basic Qualifications - 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, or NodeJS - Experience mentoring team members on best practices - Do you use AI tools daily to increase productivity in everyday work? Preferred Qualifications - Experience with big data technologies such as: Hadoop, Hive, Spark, EMR - Experience operating large data warehouses - Do you have experience communicating with users, other technical teams, and management to collect requirements, describe data modeling decisions and data engineering strategy? Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or 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. The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits . USA, NY, New York - 170,000.00 - 230,000.00 USD annually USA, WA, SEATTLE - 154,600.00 - 209,100.00 USD annually

About the Company

A

Amazon

At Amazon, we don’t wait for the next big idea to present itself. We envision the shape of impossible things and then we boldly make them reality. So far, this mindset has helped us achieve some incredible things. Let’s build new systems, challenge the status quo, and design the world we want to live in. We believe the work you do here will be the best work of your life.

Wherever you are in your career exploration, Amazon likely has an opportunity for you. Our research scientists and engineers shape the future of natural language understanding with Alexa. Fulfillment center associates around the globe send customer orders from our warehouses to doorsteps. Product managers set feature requirements, strategy, and marketing messages for brand new customer experiences. And as we grow, we’ll add jobs that haven’t been invented yet.

It’s Always Day 1
At Amazon, it’s always “Day 1.” Now, what does this mean and why does it matter? It means that our approach remains the same as it was on Amazon’s very first day – to make smart, fast decisions, stay nimble, invent, and stay focused on delighting our customers. In our 2016 shareholder letter, Amazon CEO Jeff Bezos shared his thoughts on how to keep up a Day 1 company mindset. “Staying in Day 1 requires you to experiment patiently, accept failures, plant seeds, protect saplings, and double down when you see customer delight,” he wrote. “A customer-obsessed culture best creates the conditions where all of that can happen.” You can read the full letter here

Our Leadership Principles
Our Leadership Principles help us keep a Day 1 mentality. They aren’t just a pretty inspirational wall hanging. Amazonians use them, every day, whether they’re discussing ideas for new projects, deciding on the best solution for a customer’s problem, or interviewing candidates. To read through our Leadership Principles from Customer Obsession to Bias for Action, visit https://www.amazon.jobs/principles
COMPANY SIZE
10,000 employees or more
INDUSTRY
Other/Not Classified
FOUNDED
1994
WEBSITE
http://Amazon.com/militaryroles