Amazon.com Services LLC
Technology
DataEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Data Engineer at Amazon.com Services LLC. Skills: Data engineering, ETL pipelines, Data warehousing, Dimensional modeling. Set technical direction for data warehouse. Set technical direction for ETL pipelines”
Industry & Context.
Turn open-ended questions into data products
What They're Looking For.
Must Have
5+ years of data engineering experience, Experience with data modeling, Experience with warehousing, Experience building ETL pipelines, Experience with SQL, Experience in at least one modern scripting or programming language, Experience mentoring team members on best practices
Nice to Have
Experience with big data technologies, Experience operating large data warehouses, Experience communicating with users, Experience communicating with other technical teams, Experience communicating with management, Experience collecting requirements, Experience describing data modeling decisions, Experience describing data engineering strategy
What You'll Do.
Set technical direction for data warehouse
Set technical direction for ETL pipelines
Set technical direction for reporting layer
Architect Datanet/ETLM jobs
Operate Datanet/ETLM jobs
Architect Cradle profiles
Operate Cradle profiles
Architect Andes datasets
Operate Andes datasets
Deliver on OP1/OP2 cycles
Deliver on MBR/QBR rhythms
Deliver on ad-hoc executive asks
Turn messy data into dimensional models
Set data quality standards
Set pipeline reliability standards
How You'll Work.
Team & Collaboration
Finance Managers; PM-Ts; Scientists; Engineering
Communication Scope
Executive asks
Full Job 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 techn
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