Data Engineer

Amazon.com Services LLC seeks a Data Engineer to build a greenfield finance data platform for FAIM at Amazon Ads, owning the end-to-end data warehouse, ETL pipelines, and reporting, and partnering with Finance Managers, PM-Ts, Scientists, and Engineering.

Responsibilities

• Define the technical direction for the FAIM data warehouse, ETL pipelines, and the reporting layer from start to finish.
• Architect and operate Datanet/ETLM jobs, Cradle profiles, Andes datasets, and dashboards that finance partners rely on as the single source of truth.
• Ingest telemetry from across Amazon's data ecosystem (Andes subscriptions, EDX, S3, internal services) into a clean, query-ready layer.
• Deliver on fast execution cycles, participate in regular business reviews, and respond to ad hoc executive requests with a bias toward action.
• Convert complex, multi-source data into well-documented dimensional models that scale with the organization.
• Lead code and design reviews and establish data quality and pipeline reliability standards.

Requirements

• 3+ years of data engineering experience.
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes.
• 1+ years of developing and operating large-scale data structures for business intelligence analytics with data modeling experience.
• 1+ years of developing and operating large-scale data structures for business intelligence analytics using SQL.
• Experience with data modeling, data 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 role involves a ground-up, greenfield build within Finance for one of Amazon Ads' newest initiatives in the agentic space. There are no legacy pipelines or inherited dashboards to contend with, offering a clean slate for building data infrastructure from the ground up in a fast-moving environment.

What we are building is a finance data platform that powers the FAIM (Full-Funnel Agentic Intelligence & Models) organization, supporting the next generation of agentic AI advertising products. The platform will include pipelines and models that translate raw data into actionable decisions for new products, along with self-service reporting that scales across Engineering, Science, PM-T, and Design for multiple AI native advertising products.

This is a startup team within Amazon Ads Finance, backed by an ambitious vision and the opportunity to execute with velocity. We seek a Data Engineer who brings deep SQL proficiency and at least 3 years of production ETL experience on Redshift, Andes, or equivalent at scale, along with hands-on familiarity with the Amazon data stack including Datanet/ETLM, Cradle, Andes 3.0, Redshift Spectrum, EDX, and QuickSight. Strong dimensional data modeling judgment, Python for orchestration and tooling, and a commitment to data quality and reliability standards are essential.

The ideal candidate can operate in ambiguity, turning open-ended finance questions into robust data products with minimal scoping guidance, lead data partnerships with Finance Managers, PM-Ts, Scientists, and Engineering, and mentor more junior engineers as the team grows. AI-native experience with tools such as Kiro or Claude Code is a plus.