Data Engineer III, AWS Marketplace Demand Generation & Lifecycle Engagement

AWS Marketplace is expanding its data science capabilities within the B2B Marketing organization, and this role establishes the first dedicated data engineering function on the team. As a Data Engineer III based in Seattle, you will own the data infrastructure that supports production ML scoring, auto-nurture pipelines, attribution modeling, and customer economics frameworks across the full machine learning lifecycle.

This is a foundational hire with meaningful latitude: production ML models and live pipelines already exist, and the groundwork from the past two years sets the stage for you to define how the architecture evolves. You will set standards and make trade-offs that balance speed and durability, cost and scalability, and short-term delivery against long-term maintainability.

What you’ll do

• Design, build, and operate production data pipelines that support ML models and analytics, including feature engineering, model scoring infrastructure, output delivery, and data quality enforcement.
• Define and own the team’s data architecture, making trade-offs across delivery timelines, maintainability, reliability, cost, and scalability.
• Build and maintain analytical datasets that connect product activity, marketing engagement, customer transactions, and revenue into query-ready models that enable new analysis.
• Deliver well-documented, maintainable code that others can extend, establishing patterns and templates that improve the overall quality of data work.
• Partner with data scientists, marketers, and cross-functional engineering teams to capture requirements, define data contracts, influence upstream producers, and support downstream self-service.

Skills and experience

• 5+ years of data engineering experience.
• Experience with data modeling, warehousing, and building ETL pipelines.
• Experience with SQL.
• Experience with at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS.
• Experience mentoring team members on best practices.

Technologies you may work with

• SQL, Python, Java, Scala, NodeJS
• Hadoop, Hive, Spark, EMR

About the scope

Your work spans the full ML lifecycle, from ingestion across multiple data platforms to feature engineering for model training, production pipeline deployment, model output delivery, and a reporting layer that makes results usable for stakeholders. The team’s ambition is to build measurement, targeting, and intelligence systems that inform marketing decisions across AWS Marketplace, including multi-touch attribution, ML-powered targeting, unit economics frameworks, experimentation, and partner intelligence.

Preferred qualifications

• Experience with big data technologies such as Hadoop, Hive, Spark, and EMR.
• Experience operating large data warehouses.

Compensation and location

• Location: Seattle, WA (onsite)
• Salary: USD 154,600 - 209,100 per year

Benefits

• Sign-on payments and restricted stock units (RSUs)
• Health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance, 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
• Parental leave