Onsite in New York, NY, this data engineering role focuses on building a greenfield finance data platform for FAIM within Amazon Ads. You will own the end-to-end data warehouse, ETL pipelines, and reporting, working closely with Finance Managers, PM-Ts, Scientists, and Engineering to shape the data foundation of next generation ad products.
Responsibilities
- Define the technical direction for the FAIM data warehouse, ETL pipelines, and the reporting layer from end to end.
- Design and operate Datanet/ETLM jobs, Cradle profiles, Andes datasets, and dashboards that finance partners rely on as the source of truth.
- Ingest telemetry from across Amazon’s data ecosystem (Andes subscriptions, EDX, S3, internal services) into a clean, query-ready data layer.
- Deliver on OP1 and OP2 cycles, support MBR/QBR rhythms, and respond to ad-hoc executive requests with a bias for action.
- Turn messy, multi-source data into well-documented dimensional models that scale with the organization.
- Lead code and design reviews while establishing data quality and pipeline reliability standards.
Requirements
- 3+ years of data engineering experience.
- 1+ year developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes.
- 1+ year developing and operating large-scale data structures for business intelligence analytics using data modeling.
- 1+ year developing and operating large-scale data structures for business intelligence analytics using SQL.
- Experience with data modeling, warehousing, and building ETL pipelines.
Technologies
- SQL
- Redshift
- Andes
- Datanet/ETLM
- Cradle
- Andes 3.0
- Redshift Spectrum
- EDX
- QuickSight
- SPICE
- Python
- Kiro
- Claude Code
- AWS Redshift
- S3
- AWS Glue
- EMR
- Kinesis
- FireHose
- Lambda
- IAM
Benefits
- Health insurance
- 401(k) matching
- Paid time off
- Parental leave
Description
This position represents a ground-up, greenfield initiative within Amazon Ads Finance, focusing on the FAIM team’s ambition to advance agentic AI advertising products. There are no legacy pipelines or inherited dashboards to contend with, allowing the candidate to shape data infrastructure from the ground up in a fast-moving environment.
What we are building includes a finance data platform that powers FAIM, the Full-Funnel Agentic Intelligence & Models team, responsible for the next generation of agentic AI advertising products. You will contribute to pipelines and models that convert raw data into actionable decisions for new products, and support self-service reporting that scales across Engineering, Science, PM-T, and Design for multiple AI-native advertising initiatives. This is a startup-like team within Amazon Ads Finance with a clear, ambitious vision and the runway to execute it well.
We seek a senior Data Engineer who brings strong SQL proficiency and at least 3 years of experience architecting and operating production ETL on Redshift, Andes, or comparable systems at scale. Hands-on expertise with the Amazon data stack, including Datanet/ETLM, Cradle, Andes 3.0, Redshift Spectrum, EDX, and QuickSight (SPICE), is essential. A solid foundation in dimensional data modeling, including fact/dim design, slowly changing dimensions, and informed denormalization and partitioning decisions, is required, along with Python for orchestration and data quality tooling. The ideal candidate will set data quality, lineage, SLA, and reliability standards, navigate ambiguity to deliver durable data products, and mentor junior engineers as the team grows. AI-native experience with automation and defect/opportunity detection using tools such as Kiro or Claude Code is highly valued.
