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Insurance Data Engineer Jobs in Bothell, WA (NOW HIRING)

Qualifications: * 3+ years in a data quality, ML data engineering or applied ML role. * Experience ... Comprehensive Benefits Package including Health, Dental, and Vision Insurance * 401(k) Retirement ...

Qualifications: * 3+ years in a data quality, ML data engineering or applied ML role. * Experience ... Comprehensive Benefits Package including Health, Dental, and Vision Insurance * 401(k) Retirement ...

Data Engineer, E-Commerce

Seattle, WA · On-site

$153K - $300K/yr

Responsibilities As a data engineer in the Data Platform E-Commerce team, you will have the ... Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with ...

data engineer sr- ST; Seattle, WA

Seattle, WA · On-site

$63.50 - $84/hr

Now Brewing - Data Engineers sr #tobeapartner From the beginning, Starbucks set out to be a ... insurance benefits. Partners have access to short-term and long-term disability, paid parental ...

Data Engineer, PV Prime Video TV - Tech

Seattle, WA · On-site

$130K - $156K/yr

As a Data Engineer, you will work in one of the world's largest and most complex data warehouse ... Amazon also offers comprehensive benefits including health insurance (medical, dental, vision ...

Data Solutions Engineer

Seattle, WA

$130K - $156K/yr

Join our team as a Data Solutions Engineer, where you will play a key role in designing and ... Life Insurance * Voluntary Accident Insurance - Self and Family * Short and Long-Term Disability

Showing results 21-40

Insurance Data Engineer information

See Bothell, WA salary details

$49.7K

$145K

$198.4K

How much do insurance data engineer jobs pay per year?

As of Aug 14, 2026, the average yearly pay for insurance data engineer in Bothell, WA is $145,008.00, according to ZipRecruiter salary data. Most workers in this role earn between $128,000.00 and $153,700.00 per year, depending on experience, location, and employer.

What is an insurance data engineer?

Insurance Data Engineers are professionals who design, build, and maintain data systems that support the needs of insurance companies. They are responsible for collecting, organizing, and processing large amounts of data from various sources to enable accurate risk assessment, pricing, claims analysis, and regulatory compliance. Their work helps insurers make data-driven decisions, improve efficiency, and enhance customer experiences by leveraging modern data technologies.

What are the key skills and qualifications needed to thrive as an insurance data engineer, and why are they important?

To thrive as an Insurance Data Engineer, you need strong expertise in data modeling, ETL processes, and a solid understanding of insurance data structures, typically supported by a degree in computer science, data engineering, or a related field. Proficiency with SQL, Python, big data platforms (like Hadoop or Spark), and experience with cloud data solutions such as AWS or Azure are commonly required, along with certifications like AWS Certified Data Analytics or Google Cloud Data Engineer. Excellent problem-solving, communication, and collaboration skills help you bridge technical and business needs while ensuring data quality. These abilities are essential for building robust data pipelines and enabling accurate data-driven decision making within insurance organizations.

What is the difference between Insurance Data Engineer vs Data Analyst in the insurance industry?

AspectInsurance Data EngineerData Analyst
Required CredentialsBachelor's in Computer Science, Data Engineering certificationsBachelor's in Statistics, Data Analysis certifications
Work EnvironmentDevelops data pipelines, manages databases, works with big data toolsInterprets data, creates reports, visualizes insights
Employer & Industry UsageInsurance companies, tech firms in insuranceInsurance firms, consulting agencies, analytics companies

Insurance Data Engineers focus on building and maintaining data infrastructure, while Data Analysts interpret data to provide insights. Both roles are essential in the insurance industry but serve different functions in data management and analysis.

How does an insurance data engineer typically collaborate with actuarial and underwriting teams?

Insurance Data Engineers work closely with actuarial and underwriting teams to ensure that the data infrastructure supports accurate risk assessment and pricing models. They often translate business requirements from these teams into technical specifications, build data pipelines to source and clean relevant data, and assist in implementing predictive analytics tools. Regular communication and collaboration are essential, as data engineers help bridge the gap between raw data and actionable insights for decision-making. This teamwork not only streamlines workflow but also enables continuous improvement of insurance products and customer experience.

What are popular job titles related to Insurance Data Engineer jobs in Bothell, WA?

For Insurance Data Engineer jobs in Bothell, WA, the most frequently searched job titles are:

What job categories do people searching Insurance Data Engineer jobs in Bothell, WA look for?

The top searched job categories for Insurance Data Engineer jobs in Bothell, WA are:

What cities near Bothell, WA are hiring for Insurance Data Engineer jobs?

Cities near Bothell, WA with the most Insurance Data Engineer job openings:

Infographic showing various Insurance Data Engineer job openings in Bothell, WA as of August 2026, with employment types broken down into 1% As Needed, 70% Full Time, 25% Part Time, and 4% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $145,008 per year, or $69.7 per hour.

Machine Learning Data Engineer

Outpost

Seattle, WA • On-site

$130 - $160/hr

Other

Medical, Dental, Vision, Retirement, PTO

Posted 7 days ago


Job description

About Us:

Outpost is building the backbone of freight. We’re reinventing how supply chain infrastructure works in America with carrier agnostic truck terminals. As a vertically integrated real estate, operations, and technology company, we acquire and operate mission-critical real estate across the country to serve the largest logistics providers in the world. Backed by $1B from Greenpoint Partners, we’re scaling and building the most valuable logistics network in the country.

We thrive on accountability, integrity, and a shared drive to raise the bar. If you’re excited to reshape the industry alongside a high-performance team with a championship mindset that executes relentlessly, welcome aboard.

Role Summary:

Our platform combines AI-powered gate automation, computer vision, and operational software to help logistics operators run smarter, faster facilities. We're a small, high-conviction team shipping real software that ends up in real yards, at real gates, moving real freight; and we're growing fast, with revenue set to grow 10X over the next 18 months.

As we onboard more customers, our computer vision system sees more camera layouts, identifier types, and edge cases than ever. We need someone to own accuracy end-to-end: measuring it, understanding why we get it wrong, and turning that into the labeled data that makes our models better. Today that's mostly measurement and curation. Once the pipeline matures and moves into maintenance mode, we expect this role to also contribute fixes to the product itself, not just flag issues for others to resolve.

Key Responsibilities:
  • Own tracking and reporting of CV accuracy metrics, per customer and per identifier type.
  • Investigate misclassifications and false negatives, categorize root causes, and identify patterns across customers and yards.
  • Curate, label, and prioritize datasets for model retraining, partnering closely with our ML and CV engineers.
  • Build and improve the continuous learning pipeline so new models ship weekly with minimal manual engineering effort.
  • Define functional acceptance criteria for CV accuracy per customer and track progress against them.
  • Translate accuracy findings into decisions the engineering team and customer-facing stakeholders can act on.
  • As the pipeline matures, expect to move from flagging issues to fixing them directly; building the labeling/preprocessing tooling, running retraining jobs, and owning fixes for the error patterns you find, not just reporting them.
What You Can Expect:
  • Direct ownership over the metric that decides whether our product works in the real world.
  • A small team that moves fast, argues in good faith, and trusts engineers to make decisions.
  • Real influence on what the ML team builds next; your findings drive the roadmap, not the other way around.
  • Problems grounded in the physical world: gates, cameras, trucks, and yards.
Qualifications:
  • 3+ years in a data quality, ML data engineering or applied ML role.
  • Experience working with computer vision or object detection systems in production.
  • Comfortable writing Python for data analysis, pipeline automation, and dataset tooling.
  • Strong analytical rigor, comfortable digging into large volumes of imagery/data to find patterns, not just running a script and reporting a number.
  • Experience with dataset annotation/labeling tools and workflows (Roboflow, Labelbox, CVAT, or similar).
  • Strong communication skills.
Preferred Qualifications:
  • Experience with continuous learning or active learning pipelines for production ML systems.
  • Familiarity with OCR systems and identifier recognition (plates, container numbers, etc.).
  • Experience partnering with customer success or support teams on quality metrics.
  • Background in QA/test engineering for ML systems.
  • Experience with Roboflow specifically.
Our Stack:

Python · Roboflow · VLM/OCR pipelines · GCP (GCS) · PostgreSQL · Snowflake · Node.js/TypeScript

Benefits:
  • Title Commensurate with Experience
  • Comprehensive Benefits Package including Health, Dental, and Vision Insurance
  • 401(k) Retirement Plan Matching
  • 18 Paid Holidays
  • Unlimited PTO
  • Friday Team Lunches
  • Base salary range: $130,000 - $160,000 annually, depending on experience and qualifications. Total compensation includes a discretionary bonus; a complete compensation and benefits summary will be provided during the interview process.

Outpost is an Equal Opportunity Employer and Prohibits Discrimination of Any Kind.

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