Data Engineer III, AWS Marketplace Demand Generation & Lifecycle Engagement

Amazon Web Services, Inc.; Seattle (WA); On-site; USD 155,000 - 209,000; Full time

Benefits offered by this job

RSUs

Health Insurance

401(k) matching

Paid time off

Parental leave

Job summary

AWS Marketplace is hiring a data engineer to join the B2B Marketing data science team in Seattle. You’ll own the infrastructure that supports production ML across the full lifecycle and shape how data architecture evolves to enable new analysis of product activity, engagement, transactions, and revenue.

You’ll design and operate production data pipelines, define data contracts, and collaborate with data scientists and marketers to deliver scalable, high-quality analytics platforms across the

Qualifications

• 5+ years of data engineering experience.
• Experience with data modeling, warehousing, and ETL pipelines.
• Proficient in SQL.
• Experience with Python, Java, Scala, or NodeJS.
• Experience mentoring team members.

Responsibilities

• Design, build, and operate production data pipelines for ML models and analytics.
• Define and own the data architecture, balancing speed, durability, cost, and scalability.
• Create analytical datasets stitching product activity, marketing engagement, transactions, and revenue.
• Produce well-documented, maintainable code with reusable patterns.
• Collaborate with data scientists and marketers to gather requirements and define data contracts.

Skills

Data engineering

Data modeling

Data warehousing

ETL pipelines

SQL

Python

Java/Scala/NodeJS

Mentoring

Tools

Hadoop

Hive

Spark

EMR

Job description

AWS Marketplace sits at the intersection of B2B discovery and revenue, and the team behind it is building measurement, targeting, and intelligence systems that drive marketing decisions. In this role, you’ll be the first dedicated data engineer on a data science team embedded within the B2B Marketing organization, owning the infrastructure that supports production ML across the full lifecycle.

This is a foundational hire with existing production ML models and live pipelines in place over the past two years. You will shape how data architecture evolves, set standards for quality and maintainability, and work closely with data scientists and marketing stakeholders to deliver capabilities that enable new analysis across product activity, engagement, transactions, and revenue.

What you will 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 speed vs. durability, cost vs. scalability, and short-term delivery vs. long-term maintainability.
• Create and maintain analytical datasets that stitch together product activity, marketing engagement, customer transactions, and revenue into query-ready models for analysis not previously possible.
• Produce well-documented, maintainable code that others can extend by establishing patterns and templates that raise the quality bar for the team.
• Partner with data scientists, marketers, and cross-functional engineering teams to gather requirements, define data contracts, influence upstream producers, and ensure downstream consumers can self-serve.

Requirements

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

Technologies

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

About the team

You will join a data science team within the B2B Marketing organization of AWS Marketplace, the AWS digital catalog where customers discover, evaluate, and purchase third-party software. The team builds multi-touch attribution models, ML-powered targeting engines, customer unit economics frameworks, experimentation platforms, and partner intelligence systems to power marketing decisions.

The team’s goal is an end-to-end intelligent B2B marketing platform where data science and AI are central to every decision. Working alongside data scientists on production AI systems will deepen your understanding of how models consume data and how engineering decisions influence AI outcomes.

Preferred qualifications

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

Benefits

• Sign-on payments and restricted stock units (RSUs).
• 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.
• Parental leave.

Location: Seattle, WA (onsite)
Salary: USD 154,600 - 209,100 per year
Experience: 5+ years