AmazonPosted 3w ago

Software Development Engineer, Marketing Measurement and Performance Science

Software Development Engineer, Marketing Measurement and Performance Science at Amazon scores 60 out of 100 on AI centrality, which makes it AI Level 3 of 4 (Works on AI) on this board. The level measures how much of the work is AI, not seniority.

US, WA, Seattlemidfull-time$144k-$194k

AI in this role

Design and build AI-native data systems and pipelines to feed causal modeling and MLOps platforms for marketing measurement.

pythonscalajava

ml-opsdata-engineeringcausal-inferencemlopsetl

Marketing Measurement and Performance Science (MAPS) measures the incremental impact of Amazon's marketing investments on customer perception, action, and purchases — covering billions in annual fixed marketing (FM) spend across the full funnel. Our outputs provide spend insights and recommendations that power total investment decisions at the S-team level for OP planning, BU-level budget allocation, and in-year spend guidance.

As an SDE II, you'll design and build the systems that transform and harmonize data from 20+ external partners — each with their own schemas, grains, cadences, and nuances — into the measurement-grade inputs that power COSMOS, Amazon's FM causal measurement framework. The problems you will coverage go beyond standard ETL responsibilities — you'll build AI-native systems that reconcile providers with incompatible definitions, handle split metric ownership, manage retroactive revisions, and maintain the immutable snapshots and deterministic joins that causal inference demands.

Key job responsibilities
- Design, develop, and maintain measurement-grade data systems at scale — ingesting, standardizing, and vending marketing data from 20+ external and internal sources that feed causal modeling and MLOps systems.
- Own full lifecycle delivery of production software on complex, ambiguous problems — from design through launch and ongoing operations — with independence and minimal guidance.
- Build automated validation pipelines and data quality frameworks that enforce contracts, detect anomalies across providers, and ensure measurement-grade integrity at every stage.
- Define statistical methods for outlier detection, diagnose root causes systematically, and determine corrective actions to maintain data trust.
- Partner across science, product, and engineering teams to scope solutions, navigate constraints, and ship the most efficient path from prototype to production.
- Write clean, well-tested code (Python, Scala, or Java) and mentor junior engineers on system design, code quality, and operational best practices.

A day in the life
Day to day, you'll build and scale multi-layer automated validation pipelines, with clear data lineage so every model run is fully reproducible. Our vision is to scale our infrastructure across new business units and geographies reaching 90%+ coverage of Amazon's FM spend, and develop self-service catalog and observability tooling that lets scientists and partner teams explore our data without filing tickets. You'll also have a direct influence on schema governance — designing systems that enforce data standards at the point of contract, detect drift from providers, and keep our specifications current as partnerships expand.

You'll collaborate closely with causal scientists, economists, product managers, and agency data ops teams — translating measurement requirements into scalable technical solutions. This is a high-ownership role where your work directly determines whether Amazon's leadership can trust the numbers behind billion-dollar marketing investment decisions.

About the team
Within MAPS, the Marketing Inputs & Data Automation (MIDA) team owns the measurement-grade data layer that sets the ceiling on what our causal models can measure, where they can operate, and how confident leadership should be in the outputs. We build and operate large-scale data infrastructure and data assets — ingesting, validating, harmonizing, and vending data from 20+ third-party providers (agencies, aggregators, publishers) across multiple Amazon business units and marketing channels, with global coverage. Our pipeline is purpose-built for the high bar of causal inference — not dashboards or reporting — requiring strict temporal integrity, historical stability, multi-layer validation, full lineage, and reproducibility at every stage.

Basic qualifications

- 3+ years of non-internship professional software development experience
- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience programming with at least one software programming language
- Experience programming with at least one modern language such as Java, C++, or C# including object-oriented design

Preferred qualifications

- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.

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, WA, Seattle - 143,700.00 - 194,400.00 USD annually

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Ml OpsData EngineeringCausal InferenceMlopsEtlPythonScalaJava

Questions you could be asked

How do you monitor a model once it's live, and how do you know it needs retraining?
Tell me about a project where data engineering was part of your work. What did you do?
Tell me about a project where causal inference was part of your work. What did you do?
Tell me about a project where mlops was part of your work. What did you do?
Tell me about a project where etl was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Ml Ops, Data Engineering, Causal Inference, Mlops, and Etl. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.

Want your resume actually rewritten for this job?

The free preview above is everything we have today. A full resume rewrite is not live yet and has no price set. Join the waitlist and we will email you if we open it.

Get new AI jobs at AI Level 3+ by email

One email a week with the new AI jobs at AI Level 3+, each rated AI Level 1 to 4 for how much AI is in the work. No recruiter spam, unsubscribe in one click.

Also alert me for new jobs at Amazon

Free. One email a week. Unsubscribe in one click.