refresh

Trending Companies

Trending

Jobs

JobsAmazon

Sr Data Engineer, AWS Marketplace & Partner Services

Amazon

Sr Data Engineer, AWS Marketplace & Partner Services

Amazon

Seattle, WA, USA

·

On-site

·

Full-time

·

3w ago

Compensation

$154,600 - $209,100

Benefits & Perks

Healthcare

401(k)

Equity

Parental Leave

Mental Health

Healthcare

401k

Equity

Parental Leave

Mental Health

Required Skills

Data engineering

SQL

Python

Data modeling

ETL

Mentoring

We're building the future of enterprise data systems - creating a canonical data product that serves as the single source of truth for data while enabling next-generation AI-powered experiences.

This isn't just moving and managing data; it's architecting coupled, intelligent systems that power both traditional analytics and agent capabilities at scale.

You will lead key core components of our multi-layered data architecture spanning raw ingestion through AI-ready semantic layers, working with modern cloud technologies. The technical challenges are substantial: distributed systems design, near real-time processing, complex transformations, data quality frameworks, and emerging AI architecture.

We are looking for someone who combines exceptional data engineering fundamentals with deep belief in AI capabilities - the ideal candidate is comfortable designing systems, delivering autonomously and thinking holistically about the future of data as a product. You will collaborate across data science, analytics, and software engineering teams with real influence on architectural decisions.

This position is part of the AWS Specialist and Partner Organization (ASP). Specialists own the end-to-end go-to-market strategy for their respective technology domains, providing the business and technical expertise to help our customers succeed. Partner teams own the strategy, recruiting, development, and growth of our key technology and consulting partners. Together they provide our customers with the expertise and scale needed to build innovative solutions for their most complex challenges.

  • Key job responsibilities

  • Champion and apply agentic development practices in daily work - leveraging agent-based assistants and tools to improve code quality and pioneer innovative approaches to data engineering challenges.

  • Own the evolution of our AI-first data platform. You will be responsible for system designs, implementing scalable frameworks, mentoring builders, and evolving data governance systems that securely enable intelligent decision-making

  • Champion data as a product and collaborate with data scientists, analysts, software and product teams to understand requirements and architect data solutions that enable both traditional analytics and agentic capabilities.

  • Design and evolve data quality frameworks and validation systems to maintain trust in our canonical datasets, including automated monitoring, anomaly detection, and remediation workflows

  • Design, build, and maintain scalable data pipelines that ingest, transform, and deliver high-quality datasets across our multi-layered architecture - from raw data landing through production ready data marts.

  • Develop and optimize data transformations using SQL and Python to support both analytical workloads and AI-ready semantic layers, ensuring data accuracy, consistency, and performance at scale.

Basic Qualifications

  • 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

Preferred Qualifications

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

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, WA, Seattle - 154,600.00 - 209,100.00 USD annually

Total Views

0

Apply Clicks

0

Mock Applicants

0

Scraps

0

About Amazon

Amazon

Amazon

Public

Amazon.com, Inc. is an American multinational technology company engaged in e-commerce, cloud computing, online advertising, digital streaming, and artificial intelligence.

10,001+

Employees

Seattle

Headquarters

Reviews

2.9

10 reviews

Work Life Balance

2.8

Compensation

3.7

Culture

2.5

Career

2.3

Management

2.1

35%

Recommend to a Friend

Pros

Good pay and compensation

Strong benefits package

Flexible scheduling options

Cons

Poor management and leadership

Limited growth and promotion opportunities

High stress and demanding work environment

Salary Ranges

2 data points

L2

L3

L4

L5

L6

L2 · Data Analyst L2

0 reports

$108,330

total / year

Base

$43,332

Stock

$54,165

Bonus

$10,833

$75,831

$140,829

Interview Experience

10 interviews

Difficulty

3.7

/ 5

Duration

21-35 weeks

Offer Rate

20%

Experience

Positive 10%

Neutral 10%

Negative 80%

Interview Process

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Phone Screen

5

Onsite/Virtual Loop

6

Team Matching

7

Offer

Common Questions

Coding/Algorithm

System Design

Behavioral/STAR

Leadership Principles

Technical Knowledge