> Markdown version of [/jobs/ext/1812374-data-engineer-amazon-ads](https://www.wearedevelopers.com/jobs/ext/1812374-data-engineer-amazon-ads). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer, Amazon Ads - **Company:** Amazon.com, Inc. - **Location:** Seattle, WA, United States - **Experience:** Expert - **Salary:** $145,300.0 - $196,600.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon S3, Big Data, Databases, Information Engineering, Extract Transform Load (ETL), Dataspaces, Data Stores, Data Warehousing, Graph Database, Identity and Access Management, Python (Programming Language), SQL Databases, Electronic Medical Records, AWS Glue, Non-relational Database, Amazon Redshift - **Published:** July 18, 2026 - **Apply:** https://dejobs.org/x/x/F3836916AF9144C5B7678D325504A77F/job/ ## About the Role * Deep SQL fluency and 3+ 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, * 3+ years of data engineering experience * 1+ years of developing and operating large-scale data structures for business intelligence analytics using ETL/ELT processes experience * 1+ years of developing and operating large-scale data structures for business intelligence analytics using data modeling experience * 1+ years of developing and operating large-scale data structures for business intelligence analytics using SQL experience * Experience with data modeling, warehousing and building ETL pipelines, * Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions * Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases) ## Description * 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 ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [How we built an AI-powered code reviewer in 80 hours](https://www.wearedevelopers.com/videos/1511-how-we-built-an-ai-powered-code-reviewer-in-80-hours) - [WeAreDevelopers LIVE - CSS is DOOMed](https://www.wearedevelopers.com/videos/1838-wearedevelopers-live-css-is-doomed) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [Hate organising your photos? Try it with 5 Terabytes](https://www.wearedevelopers.com/videos/79-hate-organising-your-photos-try-it-with-5-terabytes) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering)