Data Engineer, Deal Intelligence & Automation, AWS GDSP

About the role

The Global Deal Strategy and Programs (GDSP) organization is seeking a Data Engineer to own the data infrastructure that unlocks deal intelligence and automation capabilities across the organization. The role is responsible for designing, building, and maintaining the pipelines, data models, and platforms that enable deal teams to access precise, reliable insights from broad data sets (deal telemetry, pricing models, customer usage, pipeline signals) at scale, with speed and accuracy that hold as volume grows.

These data products serve deal strategists, pricing leaders, and senior executives who depend on them to structure, evaluate, and negotiate transformative contracts with AWS's most strategic customers. Quality, freshness, and accuracy of data outputs have direct, measurable impact on deal velocity, pricing quality, and revenue outcomes.

This is a high-visibility role. The data engineer partners closely with product management to translate analytical requirements into scalable data solutions, and with engineering teams to ensure pipelines integrate cleanly across GDSP's tooling ecosystem. The role will leverage generative AI and AWS services to raise the bar on how GDSP consumes and acts on data.

Key job responsibilities

• Build and maintain backend data infrastructure for analytical and visualization platforms, ensuring data is clean, fresh, and optimized for downstream consumption
• Translate business problem statements into technical data requirements, partnering with product management and stakeholders to define what data products to build
• Automate and optimize reporting processes to enable self-service analytics at scale, reducing manual effort and improving speed to insight
• Develop measurement frameworks and metrics that quantify deal execution performance and operational health
• Ensure data quality through monitoring, validation, auditing, and documentation of pipelines and data sources
• Leverage AWS services and generative AI to build next-generation data solutions that improve efficiency and unlock new analytical capabilities

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 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

Additional information

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.

Pay and benefits

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.

• USA, CA, San Diego - 154,600.00 - 209,100.00 USD annually
• USA, CA, San Francisco - 177,800.00 - 240,500.00 USD annually
• USA, CA, Santa Monica - 154,600.00 - 209,100.00 USD annually
• USA, IL, Chicago - 154,600.00 - 209,100.00 USD annually
• USA, MA, Boston - 154,600.00 - 209,100.00 USD annually
• USA, NY, New York - 170,000.00 - 230,000.00 USD annually
• USA, TX, Austin - 154,600.00 - 209,100.00 USD annually
• USA, TX, Dallas - 154,600.00 - 209,100.00 USD annually
• USA, VA, Arlington - 154,600.00 - 209,100.00 USD annually
• USA, WA, Seattle - 154,600.00 - 209,100.00 USD annually