Amazon logo

Data Engineer, Deal Intelligence & Automation, AWS GDSP

Amazon

San Francisco, CAJob$178–241K/yrSeen todaySeen in employer's feed today

Most applications go out cold — see where you stand first. No sign-up to start.

You apply on the employer's site, with no Olive account needed.

Watch jobs like this.

Don't just apply. Show up ready.

Olive works from this exact posting.

At a glance

Compensation
$178–241K/yr
Location
San Francisco, CA
Work Authorization
Not specified

Olive lists jobs from US employers, including remote roles you can work from the United States.

Job overview

The Data Engineer will build and maintain data infrastructure, pipelines, models, and platforms that provide deal teams with reliable insights at scale. The role partners with product management and engineering to translate analytical needs into data solutions, and uses AWS services and generative AI to improve how GDSP consumes and acts on data. Data quality and freshness support deal velocity, pricing quality, and revenue outcomes.

Skills & qualifications

RequiredNice to have

Skills

Data ModelingData WarehousingETL PipelinesSQLPythonJavaScalaNodeJSMentoringHadoopHiveSparkEMRLarge Data Warehouses

Qualifications

5+ Years Data Engineering Experience

Benefits

Medical Insurance
Dental Insurance
Vision Insurance
401(k) Match
Paid Time Off
Parental Leave

Full job description

Description

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

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.

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

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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, 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

How this job compares

Set against the 6,389 open Data Engineer jobs on Olive Jobs, counted November 7, 2026.

Pay
  • This posting$178–241K/yr
  • California median$150–235K/yr693 salary ranges
  • US median$125–208K/yr4,942 salary ranges

This range's midpoint, $209K, is 7% above the California median midpoint ($196K) — in the middle half of Data Engineer salary ranges in California.

Openings
Olive Jobs lists 903 open Data Engineer jobs in California and 6,389 across the US. 8% of them nationwide are listed as remote or flexible.
Hiring the most in California
Experience
This posting asks for at least 5 years of experience; Data Engineer postings that state a minimum ask for 5 years at the median (5,569 postings).
Education
2,510 of the 6,389 open Data Engineer jobs (39%) ask for a bachelor's degree or higher.

Counted across the open, public US postings on Olive Jobs on November 7, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.

Prepare for this role

You've read the whole posting — now see how you match it.