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

Data Engineer II, Product BI

Seattle, WA · On-site

$130K - $156K/yr

BASIC QUALIFICATIONS - 5+ years of data engineering experience - 3+ years of developing and ... Amazon also offers comprehensive benefits including health insurance (medical, dental, vision ...

Business Intelligence Engineer, WHS Data

Bellevue, WA · On-site

$57.50 - $74.75/hr

The WHS Data team is hiring a Business Intelligence Engineer (BIE). The Data team spans the ... Amazon also offers comprehensive benefits including health insurance (medical, dental, vision ...

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Showing results 1-20

Insurance Data Engineer information

See Renton, WA salary details

$50.1K

$145.9K

$199.7K

How much do insurance data engineer jobs pay per year?

As of Jul 24, 2026, the average yearly pay for insurance data engineer in Renton, WA is $145,908.00, according to ZipRecruiter salary data. Most workers in this role earn between $128,800.00 and $154,700.00 per year, depending on experience, location, and employer.

How much do insurance engineers make?

Insurance data engineers typically earn a median salary ranging from $80,000 to $120,000 annually, depending on experience, location, and industry. Senior roles or those with specialized skills in data pipelines, cloud platforms, and programming languages like Python or SQL can command higher salaries. Compensation may also include benefits such as bonuses and professional development opportunities.

What engineers make $500,000?

Senior data engineers, including those working in specialized fields like insurance data engineering, can earn $500,000 or more annually, especially with extensive experience, advanced skills in cloud platforms, and leadership roles. High compensation is often associated with seniority, complex data systems, and working in competitive markets or large organizations.

What are Insurance Data Engineers?

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.

Is AI replacing data engineers?

AI is transforming the role of data engineers by automating routine tasks such as data cleaning and integration, but it does not replace the need for skilled professionals to design, manage, and oversee data infrastructure. Data engineers are essential for building scalable data pipelines, ensuring data quality, and implementing AI solutions effectively. Their expertise remains critical in managing complex data environments and integrating AI tools into business processes.

What engineers make 300,000 a year?

Senior data engineers, including those working in specialized fields like insurance data engineering, can earn $300,000 or more annually, especially with extensive experience, advanced skills in SQL, Python, cloud platforms, and certifications. High-level roles often involve leadership, complex data architecture, and strategic decision-making, typically in large organizations or with specialized expertise.
What job categories do people searching Insurance Data Engineer jobs in Renton, WA look for? The top searched job categories for Insurance Data Engineer jobs in Renton, WA are:
What cities near Renton, WA are hiring for Insurance Data Engineer jobs? Cities near Renton, WA with the most Insurance Data Engineer job openings:

Senior Machine Learning / Data Engineer - Evaluation

VTI Aerospace

Seattle, WA • On-site

$120K - $163K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 29 days ago


Job description

Salary: DOE

About VTI Aerospace

VTI Aerospace builds AI-powered perception and pilot assist technologies to unlock the future of aviation. With offices in Bozeman, MT and Seattle, WA, we are a team of engineers and technologists from Boeing, Airbus, Aurora, and beyond. We are passionate about pushing the boundaries of autonomy and aviation safety. Our company is dedicated to advancing the field of aviation with cutting-edge solutions


The Role

As a Senior Software Engineer Evaluation, you will design and implement systems that measure and monitor the performance of our computer vision, automatic speech recognition (ASR), and small language model (SLM) systems. You will develop evaluation methodologies, benchmarking pipelines, and monitoring tools that ensure our AI systems perform reliably in real-world environments. You will help establish the evaluation standards and performance benchmarks that guide the development of all AI systems at the company.

You will work closely with machine learning and data engineering teams to evaluate model performance, identify failure modes, and guide improvements to data collection and model training, helping bring AI-powered aviation tools to market.


This role is ideal for someone who enjoys designing robust evaluation systems and uncovering insights from model performance data, and wants to have a direct impact on the quality and reliability of our AI systems.


What You'll Do

  • Define and implement evaluation methodologies for computer vision, ASR, and language systems
  • Identify and track key performance indicators (KPIs) that measure system and model effectiveness
  • Perform dataset coverage analysis to understand strengths, gaps, and biases in training and evaluation data
  • Identify model deficiencies and collaborate with ML engineers to improve training data and model performance
  • Build scalable model evaluation pipelines in Python for automated benchmarking and regression testing
  • Design and maintain systems for monitoring model performance and drift in production environments
  • Architect data models and storage systems for evaluation results using relational and time-series databases
  • Build dashboards and reporting tools to visualize model performance and evaluation metrics
  • Collaborate with ML and data engineering teams to improve evaluation workflows and data pipelines
  • Contribute to ground-truth data pipelines and processes that support reliable evaluation


What We're Looking For

  • 5+ years of experience developing production software systems in Python
  • Strong experience designing and implementing data processing or analysis pipelines
  • Experience building systems for machine learning evaluation, experimentation, or benchmarking
  • Experience working with large datasets and building scalable data workflows
  • Familiarity with statistical methods, experimental design, and model performance analysis
  • Experience building automated pipelines using tools such as Airflow or similar orchestration frameworks
  • Experience working with evaluation or experiment tracking tools such as MLflow or similar systems
  • Experience designing data models and working with relational databases and time-series data
  • Strong collaboration skills and ability to work closely with machine learning and data engineering teams


Bonus Points

  • Experience working with computer vision, ASR, or language models in production environments
  • Experience using PyTorch or other deep learning frameworks
  • Experience evaluating multimodal or large-scale AI systems
  • Experience building monitoring systems for ML models in production
  • Experience designing dataset analysis or data quality tooling
  • Experience building dashboards or monitoring tools using Grafana or similar platforms


Why You'll Love Working Here

  • Opportunity to work on meaningful problems in aviation and deliver products to industry at a rapid pace
  • Small team with significant impact on company direction
  • Collaborative and innovative environment
  • Competitive compensation and benefits
  • Opportunities for growth and leadership


Location

Work arrangement: On-site

Primary location: Seattle or Bozeman


Compensation & Benefits

Salary range: DOE

Benefits may include:

Health, dental, and vision insurance
Retirement plan or 401(k)
Paid time off and holidays
Professional development opportunities


Equal Opportunity Statement

VTI is proud to be an equal opportunity employer. We value diverse perspectives and encourage candidates from all backgrounds to apply