Role at a glance
- Job function
-
AI & Data Data Engineering
- Salary
- Not yet verified Check the description for pay details; an amount or pay period has not been verified.
- Location
- Seattle, Washington, United States New York, New York, United States
- Work arrangement
- On-site
- Experience
- Basic Qualifications - 1+ years of data engineering experience - Experience with data modeling, warehousing and building ETL pipelines - Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala) - Experience with one or more scripting language (e.g., Python, KornShell)
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Role Summary
The Data Engineer builds and operates infrastructure and production data and ML systems supporting Amazon Advertising’s self-service support experiences. The role also develops agentic workflows intended to improve advertisers’ ability to resolve issues themselves.
What You'll Do
- Design, build, and maintain data infrastructure, including data lakes, warehouses, and streaming systems.
- Deploy ML models to production and manage CI/CD, model serving, monitoring, and rollback strategies.
- Develop and optimize ETL/ELT pipelines for performance, reliability, and cost efficiency, with observability and SLA adherence.
- Develop agentic workflows that reason, plan, and act to improve advertiser self-service experiences.
- Maintain production reliability and scalability, and lead incident response and root-cause analysis.
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Required: 1+ years of data engineering experience; experience with data modeling, warehousing, and ETL pipelines; experience with one or more query languages (SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, or Scala); experience with one or more scripting languages (Python or KornShell).
Required
- 1+ years of data engineering experience
- Data modeling, warehousing, and ETL pipeline experience
- One or more query languages: SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, or Scala
- One or more scripting languages: Python or KornShell
Preferred
- Big data technologies such as Hadoop, Hive, Spark, or EMR
- An ETL tool such as Informatica, ODI, SSIS, BODI, or Datastage
Original job description
Content provided by the employer
Original job description
Content provided by the employer
Key job responsibilities
In this role, you'll be the engineering backbone of our team — owning the systems that power intelligent, self-service experiences for advertisers at scale. You'll deploy ML models into production, optimize data pipelines for performance and reliability, and lead the development of agentic workflows that autonomously reason and act on behalf of our customers.
## Key Responsibilities
- **Infrastructure Ownership** — Design, build, and maintain scalable data infrastructure (data lakes, warehouses, streaming systems) that supports our analytics and ML workloads
- **Production Model Deployment** — Own the end-to-end lifecycle of deploying ML models into production, including CI/CD pipelines, model serving, monitoring, and rollback strategies
- **Pipeline Engineering & Optimization** — Develop and fine-tune ETL/ELT pipelines for performance, reliability, and cost efficiency; instrument for observability and SLA adherence
- **Agentic AI Development** — Drive the design and implementation of agentic workflows — autonomous systems that reason, plan, and take actions to improve advertiser self-service experiences
- **Reliability & Scalability** — Ensure production systems meet uptime, latency, and throughput targets; lead incident response and root-cause analysis
- **Collaboration** — Partner with Data Scientists, Applied Scientists, Product, and Content teams to translate research into production-ready solutions that help advertisers help themselves
Basic Qualifications
- 1+ years of data engineering experience- Experience with data modeling, warehousing and building ETL pipelines
- Experience with one or more query language (e.g., SQL, PL/SQL, DDL, MDX, HiveQL, SparkSQL, Scala)
- Experience with one or more scripting language (e.g., Python, KornShell)
Preferred Qualifications
- Experience with big data technologies such as: Hadoop, Hive, Spark, EMR- Experience with any ETL tool like, Informatica, ODI, SSIS, BODI, Datastage, etc.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including 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, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, NY, New York - 111,400.00 - 185,000.00 USD annually
USA, WA, SEATTLE - 101,300.00 - 160,000.00 USD annually
About the company
amazon
Large Enterprise
Amazon is a global leader in e-commerce and cloud computing, founded in 1994 by Jeff Bezos. Initially starting as an online bookstore, it has since expanded its offerings to include a vast range of products and services, including electronics, fashion, and digital content. With Amazon Web Services (AWS), the company also provides powerful cloud solutions to businesses around the world. Known for its innovation, customer-centric approach, and commitment to operational efficiency, Amazon continues to shape the future of retail and technology, consistently seeking new ways to enhance customer experiences.