Data Engineer, SMGS Business Insights and Operations
Company: Amazon
Location: Seattle
Posted on: April 2, 2026
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Job Description:
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 AmazeCon (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. - 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 - 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
QuickSight, 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
Keywords: Amazon, Seattle , Data Engineer, SMGS Business Insights and Operations, IT / Software / Systems , Seattle, Washington