AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services.

At Amazon, we're working to be Earth's most customer-centric Company and Earth's Best Employer. To get there, we need exceptionally talented, bright, and driven people. Within AWS, the Business Insights and Operations team serves as a central business operations and analytics function that supports the AWS Industries organization with actionable insights, data, and dashboards to gauge performance and refine our strategy. We also work closely with business operations and engineering teams in planning, designing, executing, and implementing data solutions, automating mechanisms, and driving business cadences. We are seeking an experienced Data Engineer to design, build, and maintain scalable data pipelines and infrastructure that power our data-driven organization. Candidates should have advanced data engineering skills and experience building solutions that can scale across large, complex datasets. Beyond data engineering expertise, the ideal candidate would also have broad technical skills including SQL proficiency, Python development, ETL/ELT design, and experience working with AWS data services.

Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we're building an environment that celebrates knowledge sharing and mentorship. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded professional and enable them to take on more complex tasks in the future.

Key job responsibilities

Design and implement complex data pipelines and models that power business-critical analytics and reporting

Drive end-to-end delivery of scalable, reliable, and low-cost data solutions from production systems into the data lake

Develop new data processing patterns and frameworks to optimize performance and reliability of data infrastructure

Lead technical design and implementation of ETL/ELT solutions using AWS services including EMR, Redshift, Glue, Lambda, and S3

Collaborate with business owners and stakeholders to understand data requirements and translate them into technical solutions

Create robust data quality and monitoring solutions to ensure data accuracy, completeness, and availability

Mentor junior team members in data engineering best practices and contribute to a culture of continuous improvement

About the team

About AWS

Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the 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:

Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and Amaze Con (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

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 in the cloud.

Basic Qualifications

• Experience with big data technologies such as: Hadoop, Hive, Spark, EMR
• Bachelor's Degree in Computer Science, Mathematics, Statistics, Engineering, or equivalent experience
• 5+ years of designing and implementing data pipelines and ETL/ELT processes
• Experience with SQL, Advanced SQL scripting
• Experience with Python development for data engineering

Preferred Qualifications

• Knowledge of batch and streaming data architectures like Kafka, Kinesis, Flink, Storm, Beam
• Experience with AWS data services (EMR, Redshift, Glue, S3, Lambda or equivalent)
• Familiarity with AI technologies (FM, MCP server, Quicksuite)
• Experience with data governance frameworks (including data quality, lineage, and cataloging)
• Experience with data visualization tools (Amazon Quick Sight, Tableau, or equivalent)
• Experience with infrastructure-as-code and CI/CD pipelines for data engineering workflows
• Experience working in a Sales Operations or business analytics environment

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