Data Engineer, Amazon Ads

Amazon • Seattle, WA

1d • $154,600 - $230,000 • Onsite

About The Position

This is a ground-up, greenfield build for Finance within Amazon Ads, focusing on one of Amazon Ads' newest ventures in the agentic space. The role involves building a finance data platform for the FAIM org (Full-Funnel Agentic Intelligence & Models), which is developing the next generation of agentic AI advertising products. The platform will include pipelines and models to transform raw data into decisions for new products, as well as self-service reporting for Engineering, Science, PM-T, and Design teams across multiple AI-native advertising products. This is a startup team within Amazon Ads Finance with an ambitious vision and the resources to build it correctly from the start.

Requirements

• 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
• 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
• Do you use AI tools daily to increase productivity in everyday work?

Nice To Haves

• 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?

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

Benefits

• 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
• parental leave
• sign-on payments
• restricted stock units (RSUs)

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed