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Data Science Engineer Jobs in Seattle, WA (NOW HIRING)

The Research Data Science team builds innovative solutions for iSpot's audience measures ... Work with our Engineering teams to design and implement efficient data pipelines to collect ...

Our Growth and Data Science team spans both Microsoft's Developer Division and AI Foundry. We accelerate CoreAI's mission by delivering insights, reporting, models, and tools that guide product ...

You will partner closely with Product, Engineering, Operations, Data Platforms, and executive ... Define and drive the strategic direction for AI and Data Science capabilities across Customer Care ...

You will partner closely with Product, Engineering, Operations, Data Platforms, and executive ... Define and drive the strategic direction for AI and Data Science capabilities across Customer Care ...

The Research Data Science team builds innovative solutions for iSpot's audience measures ... Work with our Engineering teams to design and implement efficient data pipelines to collect ...

The Research Data Science team builds innovative solutions for iSpot's audience measures ... Work with our Engineering teams to design and implement efficient data pipelines to collect ...

What you'll do Docusign's Product Data Science team is looking for a Data Scientist Intern to ... Partner closely with the product managers, user researchers, engineers, and leadership to capture ...

What you'll do Docusign's Product Data Science team is looking for a Data Scientist Intern to ... Partner closely with the product managers, user researchers, engineers, and leadership to capture ...

Data Engineer, PXT Central Science

Seattle, WA · On-site

$130K - $156K/yr

The PXT Central Science team is looking for a Data Engineer. This individual will join a team of economists and scientists to own and accelerate science and analytics in our rapid employee ...

With sound business acumen and a foundational understanding of supply chain, you will lead a high-performing team of data analysts, scientists, and programmers to deploy supply chain solutions. You ...

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Data Science Engineer information

See Seattle, WA salary details

$50.6K

$147.6K

$202K

How much do data science engineer jobs pay per year?

As of Jun 16, 2026, the average yearly pay for data science engineer in Seattle, WA is $147,621.00, according to ZipRecruiter salary data. Most workers in this role earn between $130,300.00 and $156,500.00 per year, depending on experience, location, and employer.

Is AI replacing data scientists?

AI is transforming the role of data science engineers by automating routine tasks and enabling more advanced analysis, but it does not replace the need for skilled professionals who interpret data, develop models, and ensure ethical use. Data scientists and data science engineers are increasingly working alongside AI tools to enhance decision-making and innovation. The demand for expertise in programming, statistical analysis, and machine learning remains strong in the industry.

What are the key skills and qualifications needed to thrive in the Data Science Engineer position, and why are they important?

A Data Science Engineer should have a strong background in statistics, machine learning, programming (typically Python or R), and data engineering, often supported by a degree in computer science, engineering, or a related field. Familiarity with data processing frameworks (like Spark or Hadoop), cloud platforms (AWS, GCP, or Azure), and certifications in data science or cloud technology are highly valued. Excellent problem-solving skills, communication abilities, and collaboration are essential soft skills for working effectively in cross-functional teams. These competencies enable Data Science Engineers to build scalable data solutions, deliver actionable insights, and drive business impact.

What are the typical daily responsibilities of a Data Science Engineer?

Data Science Engineers typically spend their days designing and building data pipelines, preparing and cleaning large datasets, and developing machine learning models to solve business problems. They work closely with data scientists, software engineers, and business stakeholders to translate requirements into scalable technical solutions. Responsibilities also include deploying models to production, monitoring their performance, and iterating on solutions based on feedback. This role offers a dynamic mix of coding, data analysis, and teamwork, making each day varied and intellectually engaging.

Is 40 too late for data science?

Data Science Engineers can enter the field at any age, as success depends on skills, experience, and continuous learning. Many professionals transition into data science later in their careers by acquiring relevant knowledge in programming, statistics, and tools like Python or R. Age is less important than demonstrated expertise and the ability to adapt to evolving technologies.

What is the 80 20 rule in data science?

The 80/20 rule in data science suggests that roughly 80% of the results come from 20% of the efforts or features. Data scientists often use this principle to focus on the most impactful variables, optimize models, and prioritize tasks for efficiency.

What is a Data Science Engineer job?

A Data Science Engineer is a professional who bridges the gap between data science and software engineering. They focus on designing, building, and maintaining scalable data pipelines, infrastructure, and machine learning models for production use. Their role involves data preprocessing, model deployment, performance optimization, and integrating AI solutions into applications. They work closely with data scientists, software engineers, and DevOps teams to ensure efficient data workflows.

What does a data science engineer do?

A data science engineer designs, develops, and maintains data pipelines and infrastructure to support data analysis and machine learning models. They work with large datasets, use programming languages like Python or Scala, and often collaborate with data scientists and software engineers to implement scalable data solutions.
What are the most commonly searched types of Data Science Engineer jobs in Seattle, WA? The most popular types of Data Science Engineer jobs in Seattle, WA are:
What are popular job titles related to Data Science Engineer jobs in Seattle, WA? For Data Science Engineer jobs in Seattle, WA, the most frequently searched job titles are:
What job categories do people searching Data Science Engineer jobs in Seattle, WA look for? The top searched job categories for Data Science Engineer jobs in Seattle, WA are:
Infographic showing various Data Science Engineer job openings in Seattle, WA as of June 2026, with employment types broken down into 1% As Needed, 86% Full Time, 10% Part Time, and 3% Contract. Highlights an 87% Physical, 6% Hybrid, and 7% Remote job distribution, with an average salary of $147,621 per year, or $71 per hour.
Data Engineer, Data : Science Engineering, AWS Marketing, Data : Science Engineering, AWS Marketing

Data Engineer, Data : Science Engineering, AWS Marketing, Data : Science Engineering, AWS Marketing

Amazon

Seattle, WA

$130K - $156K/yr

Full-time

Posted 23 days ago


Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 6,856 frontline employees who took The Breakroom Quiz

6th of 39 rated national retailers


Job description

Sales, Marketing and Global Services (SMGS)
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.
Mission Statement
The AWS Marketing Data: AI Science, Analytics and Engineering (D:SE) team owns analytics, reporting and self-service tooling, data representation, machine learning models, measurement, valuation and economics products for AWS Marketing

We are the central data and science organization, and we work with different teams in AWS Marketing to drive better measurement, increase experimentation velocity, improve data access and analytical self-service, deploy and test ML-powered targeting models, drive higher economic value, and empower strategic decisions with business deep dives. We enable other analytics, BI, and science teams across AWS Marketing through mechanisms, partnerships and scalable tools. We work globally as a central team and establish standards, benchmarks, and best practices for use throughout AWS Marketing.
Overview
Would you like to support increasing customer base and the revenue for AWS, a market-leading cloud offering

Would you like to be part of a team focused on increasing awareness and adoption of the AWS platform by analyzing customer's behavior on and outside AWS websites. Do you want to empower our AWS Marketing organization make data-driven decisions that further establish AWS as leader in the cloud computing world?
As a Data Engineer at AWS, you will be working in a large, extremely complex and dynamic data warehousing environment. We are looking for someone with the uncanny ability to integrate multiple heterogeneous data sources with AWS Marketing Data Warehouse - Jarvis and build efficient, flexible, and scalable data warehouse and reporting solutions.

You should be enthusiastic about learning new technologies and be able to implement solutions using these technologies to enable upgrades of the existing platform. You should have excellent business and communication skills and be able to work with business owners to develop and define key business questions, then build the data sets that answer those questions. You should be expert at designing, implementing, and operating stable, scalable, low cost solutions to flow data from production systems into the data warehouse and into end-user facing reporting applications.

Above all you should be passionate about working with huge data sets and someone who loves to bring datasets together to answer business questions and drive growth.
At AWS, you have control over every layer you build. Instead of owning a small slice of an existing service, you will own a core segment of a growing marketing platform serving 1000s of internal customers and millions of external customers. You will build on multiple AWS services and have opportunities to engage directly with those teams to improve our core offerings

At AWS, we work with our customers on a daily basis to prove out our ideas, gather feedback, and improve the platform.
A day in the life
- Design, implement, and support a platform providing ad-hoc access to large datasets
- Interface with other technology teams to extract, transform, and load data from a wide variety of data sources using SQL
- Build robust and scalable data integration (ETL) pipelines using SQL, Python and AWS services such as Data Pipelines, Glue
- Implement data structures using best practices in data modeling, ETL/ELT processes, and SQL/Redshift
- Interface with business customers, gathering requirements and delivering complete reporting solutions
- Build and deliver high quality datasets to support business analyst and customer reporting needs
- Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for customers
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.


What Amazon employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Amazon logo

About Amazon

Sourced by ZipRecruiter

Amazon.com, Inc., commonly known as Amazon, is an American multinational technology company. It was founded by Jeff Bezos in 1994 and initially started as an online marketplace for books. Since then, Amazon has expanded its operations and become one of the largest e-commerce companies in the world. Amazon's primary business is its online retail platform, where customers can purchase a vast array of products, including electronics, clothing, books, home goods, and much more. The company offers a convenient and user-friendly shopping experience, with features such as fast shipping, customer reviews, and personalized recommendations. In addition to its e-commerce platform, Amazon has diversified its business into various other areas. One of its notable ventures is Amazon Web Services (AWS), a comprehensive cloud computing platform that provides services such as storage, compute power, and database management to individuals and businesses. AWS has become a leader in the cloud computing industry, powering many websites and applications worldwide. Amazon has also developed its own consumer electronics, including the popular Amazon Kindle e-reader, Fire tablets, Fire TV streaming devices, and the Alexa-powered Echo smart speakers. The Alexa voice assistant, integrated into these devices, allows users to interact with their devices using voice commands, perform tasks, and access information. Furthermore, Amazon has expanded into media and entertainment. It operates Prime Video, a streaming service that offers a wide range of movies, TV shows, and original content. Amazon Music provides a platform for streaming and purchasing digital music, while Audible offers audiobooks and other audio content. The company's commitment to customer satisfaction and convenience is demonstrated by its membership program, Amazon Prime. Prime members receive various benefits, including free two-day shipping, access to streaming services, exclusive deals, and more.

Industry

It services, book publishers, retail, real estate and computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Seattle, WA, US