Senior Data Engineer - Marketing Analytics & ML Pipelines

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

Benefits offered by this job

Health insurance

RSU eligibility

401(k) matching

Paid time off

Job summary

Amazon Web Services (AWS) is seeking a foundational data engineer to join the B2B Marketing organization within AWS Marketplace. You will own and shape data infrastructure powering marketing intelligence, including ML scoring engines, auto-nurture pipelines, attribution, and customer economics frameworks.

You will design production data pipelines, define architecture, and collaborate with data scientists and marketers to deliver self-serve data and analytics across business units.

Qualifications

• 5+ years of data engineering experience.
• Experience with data modeling, warehousing and building ETL pipelines.
• Experience with SQL.
• Experience in a modern scripting or programming language (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 team's data architecture with trade-offs on speed, cost, and scalability.
• Build analytical datasets joining product activity, marketing engagement, transactions, and revenue data.
• Produce well-documented, maintainable code with reusable patterns.
• Partner with data scientists, marketers, and engineers to gather requirements and ensure self-serve data.

Skills

Data engineering

Data modeling

Data warehousing

ETL pipelines

SQL

Python

Java

Scala

NodeJS

Mentoring

Tools

Hadoop

Hive

Spark

EMR

Job description

Amazon Web Services (AWS) is seeking a foundational data engineer to join the B2B Marketing organization within AWS Marketplace. You will own and shape data infrastructure powering marketing intelligence, including ML scoring engines, auto-nurture pipelines, attribution, and customer economics frameworks.

You will design production data pipelines, define architecture, and collaborate with data scientists and marketers to deliver self-serve data and analytics across business units.