GDSP 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
About the team
The team builds products that power how GDSP operates. Reporting and tooling that are held to the highest standards of clarity, reliability, and scalability.
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
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, CA, San Francisco - 177,800.00 - 240,500.00 USD annually
USA, CA, Santa Monica - 154,600.00 - 209,100.00 USD annually
USA, GA, Atlanta - 154,600.00 - 209,100.00 USD annually
USA, IL, Chicago - 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, VA, Herndon - 154,600.00 - 209,100.00 USD annually
USA, WA, Seattle - 154,600.00 - 209,100.00 USD annually
