Data Engineer II, AWS Marketplace and Partner Services

Full Job Description

AWS Marketplace and Partner Services (AMPS) is a fast-growing organization that supports Sellers, Partners, Partner Development Managers, and AWS Marketplace customers. The AMPS team is driven by the mission to provide the best partner experience worldwide. Data Engineering is a horizontal layer that supports all foundational data needs for the organization.

As a Data Engineer on the AMPS team, you will work directly with Software Engineering, Business Intelligence, Data Science, and Product teams to continuously improve and build our data infrastructure, data models, tools, and data pipelines. Your work will directly influence organizational insights, customer-facing features, and machine learning models.

To be successful in this role, you should have strong database design skills, comfort with large data sets, and an eagerness to build with GenAI solutions. You should have a passion for data and analytics with the technical skills needed to build for scale and automation.

Key job responsibilities

• Design and implement next-generation data pipelines and business intelligence solutions using AWS services such as Redshift, Kinesis, EMR, Glue, and Lambda
• Build and deliver high-quality data architecture and pipelines to support business analysts, data scientists, and customer reporting needs
• Interface with other technology teams to extract, transform, and load data from a wide variety of sources, creating coherent logical data models that drive physical design
• Continually improve reporting and analysis processes, automating self-service support for customers and ensuring data quality across pipelines
• Participate in code reviews, design discussions, and team planning while mentoring peers on how team data solutions are constructed and operated

A day in the life You will collaborate with Software Engineers, Product Managers, Data Scientists, and Business Intelligence Engineers to design, plan, and deliver high-priority data initiatives serving internal stakeholders and AWS customers. You will build automated, fault-tolerant, and scalable data solutions using technologies such as Spark, EMR, Python, Redshift, Glue, and S3. You will also evaluate and improve our architecture, tooling, and codebase to maximize performance and scalability. As you deliver projects independently and lead efforts end to end, you will take on increasingly complex scope and grow into broader responsibilities across the team.

About the team We are the Data Engineering team in AMPS, powering analytics for the AWS Marketplace Platform. Our data serves external Marketplace sellers and hundreds of internal Finance, Sales, and Partner stakeholders. We are building an enterprise-grade, AI-native Data Platform and a unified Canonical Data Model on Redshift and Data Lake — designing ETL frameworks, migrating billions of rows, and treating data quality and security as first-class concerns. We work across Redshift, Airflow, Glue, S3, and CDK, and we are early adopters of GenAI in our engineering workflow. Come own hard, ambiguous problems end to end.

AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events build stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.

Diverse Experiences

AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Why AWS?

Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture

AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.

Mentorship & Career Growth

We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Work/Life Balance

We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve.

Basic Qualifications

• 5+ years of data engineering experience
• Experience with data modeling, warehousing and building ETL pipelines
• Experience programming with at least one modern language such as C++, C#, Java, Python, Golang, PowerShell, Ruby
• 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
• 3+ years of big data technologies such as AWS, Hadoop, Spark, Pig, Hive, Lucene/SOLR or Storm/Samza experience

Preferred Qualifications

• Master's degree in statistics, business analytics, data analytics, data science, computer science or related field

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 - 132,100.00 - 178,800.00 USD annually

5+ years of data engineering experience Experience with data modeling, warehousing and building ETL pipelines Experience programming with at least one modern language such as C++, C#, Java, Python, Golang, PowerShell, Ruby 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience 3+ years of big data technologies such as AWS, Hadoop, Spark, Pig, Hive, Lucene/SOLR or Storm/Samza experience