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Full Stack Data Engineer Jobs in Bellevue, WA (NOW HIRING)

We are seeking a highly skilled Full Stack Developer with strong Data Engineering experience and proven expertise in API Development (must-have) to join our dynamic team. The ideal candidate will be ...

You build the AI-powered features customers touch every day data preparation, analysis ... full-stack-engineer- bellevue?utm_source=dstribute & utm_medium=job+boards & utm_campaign=golden ...

Collaborate across Adobe's platform, infrastructure, data, and security teams to ensure the Agentic ... Full-stack engineering depth sufficient to contribute across the agent's entire surface area ...

They are seeking a Full Stack Engineer to design and build features across both front-end and back-end systems, ensuring a seamless experience for customers and internal teams. Responsibilities : • ...

Company Description At Divensi, we believe that businesses are profoundly impacted by data ... Every engineer is involved in the entire software development lifecycle (SDLC), everything from ...

Company Description At Divensi, we believe that businesses are profoundly impacted by data ... Every engineer is involved in the entire software development lifecycle (SDLC), everything from ...

About the role We're looking for a Full-Stack engineer who wants to build, own, and ship end-to-end ... Experience working on data-intensive or complex applications * Familiarity with fintech or ...

Full Stack Engineer

Seattle, WA · On-site

$140K - $185K/yr

The role As a Full Stack Engineer, you will design and build features across the full application stack, helping Vale deliver a seamless experience for customers, operators, and internal teams.

Full Stack Engineer

Seattle, WA · On-site

$140K - $185K/yr

The role As a Full Stack Engineer, you will design and build features across the full application stack, helping Vale deliver a seamless experience for customers, operators, and internal teams.

## Senior Full Stack Software Engineer - Catalogs, Hierarchy & OrgMDM (Hybrid - Seattle, WA ... Drive data quality at scale.** You'll build validation, canonicalization, and entity resolution ...

Full Stack Engineer

Seattle, WA · On-site

$140K - $185K/yr

The role As a Full Stack Engineer, you will design and build features across the full application stack, helping Vale deliver a seamless experience for customers, operators, and internal teams.

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Full Stack Data Engineer information

See Bellevue, WA salary details

$50.2K

$152.1K

$215K

How much do full stack data engineer jobs pay per year?

As of Aug 13, 2026, the average yearly pay for full stack data engineer in Bellevue, WA is $152,107.00, according to ZipRecruiter salary data. Most workers in this role earn between $125,300.00 and $178,300.00 per year, depending on experience, location, and employer.

What is the difference between Full Stack Data Engineer vs Data Scientist?

AspectFull Stack Data EngineerData Scientist
CredentialsBachelor's/Master's in CS, Data Engineering certificationsBachelor's/Master's in CS, Data Science or related fields
Work EnvironmentBuild data pipelines, manage databases, develop APIsAnalyze data, create models, generate insights
Industry UsageTech, finance, healthcare, where data infrastructure is keyResearch, analytics, product development teams

Full Stack Data Engineers focus on building and maintaining data infrastructure, integrating data from various sources, and ensuring data availability. Data Scientists analyze data, develop models, and generate insights. While both roles require strong technical skills, Full Stack Data Engineers are more involved in data pipeline development, whereas Data Scientists focus on data analysis and modeling.

What are the key skills and qualifications needed to thrive as a full stack data engineer, and why are they important?

To thrive as a Full Stack Data Engineer, you need strong expertise in data modeling, ETL processes, and proficiency in both backend (e.g., Python, Java) and frontend (e.g., JavaScript, React) development, often supported by a degree in computer science or a related field. Familiarity with cloud platforms (such as AWS or Azure), big data tools (like Spark or Hadoop), and database systems (SQL and NoSQL) is typically required, and certifications in these technologies are advantageous. Excellent problem-solving, communication, and collaboration skills help you bridge gaps between data, development, and business teams. These skills ensure you can design, build, and maintain scalable data solutions that meet organizational needs efficiently.

How does a full stack data engineer typically balance responsibilities between backend data infrastructure and frontend data presentation tasks?

Full Stack Data Engineers are often required to split their time between developing robust backend data pipelines and creating user-facing tools or dashboards that visualize data insights. This dual responsibility means you'll need to prioritize tasks based on project needs, effectively collaborating with data scientists, analysts, and frontend developers. Communication is key, as you'll bridge gaps between technical teams and business stakeholders, ensuring data flows seamlessly from source systems to end users. Over time, many engineers find opportunities to specialize further or move into leadership roles overseeing data architecture and team strategy.

What is a full stack data engineer?

A Full Stack Data Engineer is a professional who designs, builds, and maintains the entire data pipeline, from data collection and storage to processing and visualization. They work with both the backend infrastructure (such as databases, data warehouses, and ETL processes) and frontend tools (like dashboards or reporting systems) to ensure data is accessible and usable for analytics. Full Stack Data Engineers possess skills in programming, database management, data modeling, cloud platforms, and often data visualization, allowing them to manage every stage of data flow within an organization.

What are popular job titles related to Full Stack Data Engineer jobs in Bellevue, WA?

For Full Stack Data Engineer jobs in Bellevue, WA, the most frequently searched job titles are:

What cities near Bellevue, WA are hiring for Full Stack Data Engineer jobs?

Cities near Bellevue, WA with the most Full Stack Data Engineer job openings:

Infographic showing various Full Stack Data Engineer job openings in Bellevue, WA as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, and 4% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $152,107 per year, or $73.1 per hour.

Senior Full Stack Data Scientist

Garuda Ventures

Seattle, WA • On-site

$120 - $150/hr

Other

Posted 7 days ago


Job description

About Arkero

Arkero is an AI company building intelligent automation solutions for professional sports organizations, ticketing platforms, and live entertainment businesses. We were founded on the conviction that the passionate professionals running these institutions deserve tools that amplify their expertise, not slow them down.

Our AI works alongside sports professionals, automating repetitive workflows so teams can focus on strategy, creativity, and the decisions that drive real business impact. If you're excited about applying cutting-edge AI to one of the most data-rich industries in the world, we'd love to hear from you.

The Role

We are seeking a highly skilled and innovative Senior Full Stack Data Scientist to join our dynamic team. The ideal candidate will possess a strong background in both data science and software engineering, with a focus on developing end-to-end data-driven solutions. This role offers an exciting opportunity to leverage advanced analytics and cutting-edge technologies to drive impactful business outcomes. You'll work across the full data science lifecycle: from data acquisition and feature engineering to model development, dashboard delivery, and stakeholder communication.

Key Responsibilities
  • Design, develop, and deploy end-to-end AI and machine learning solutions — from data acquisition and feature engineering through model training, validation, and production deployment.
  • Build and maintain robust data pipelines for acquiring, cleaning, and preprocessing large-scale datasets from varied and often messy sources, with a strong focus on data quality and reliability.
  • Leverage AI and advanced analytics techniques to develop innovative, scalable solutions that drive impactful business outcomes.
  • Optimize model and AI system performance through feature engineering, hyperparameter tuning, rigorous validation, and continuous monitoring — treating calibration and drift as ongoing operational concerns.
  • Build scalable, maintainable software to integrate AI and data science workflows with existing systems, enabling seamless data-driven decision-making across the organization.
  • Establish and maintain monitoring mechanisms to proactively detect model drift, data quality issues, and performance degradation — identifying root causes and validating fixes.
  • Work closely with engineers, software developers, and business stakeholders to translate ambiguous business questions into structured AI-driven analyses with explicit assumptions and clear, audience-appropriate communication.
Required Qualifications
  • Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field.
  • 7+ years of hands-on experience across the full data science stack — from raw data acquisition and feature engineering to model deployment and production monitoring.
  • Experience with Claude Code, Codex, or other AI coding agents in delivering high quality data science work.
  • Strong proficiency in Python and SQL, with a solid foundation in software engineering best practices including version control, maintainable code, and working effectively in a shared codebase.
  • Deep understanding of machine learning algorithms, statistical modeling, and model validation — with proven experience productionizing ML models including drift detection, calibration, and performance monitoring.
  • Demonstrated experience with generative AI and large language models, including prompt engineering, fine-tuning, or integrating AI APIs into production workflows.
  • Experience developing and deploying end-to-end data science solutions in cloud environments, with familiarity across the modern AI/ML tooling ecosystem.
  • Strong written and verbal communication skills — able to translate complex AI-driven findings into clear, actionable insights for both technical and non-technical audiences.
Preferred Qualifications
  • Experience on a small or startup team — comfortable wearing engineering, analyst, and PM hats in the same week.
  • Experience with sports and ticketing platforms and data ecosystems such as Ticketmaster, SeatGeek, or similar.
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