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Insurance Data Engineer Jobs in Raleigh, NC (NOW HIRING)

LexisNexis

Senior Data Scientist III

Raleigh, NC · On-site +1

$115K - $192K/yr

You will work closely with other data scientists and engineers to design, develop, and deploy ... Short-and-Long Term Disability, Life and Accidental Death Insurance, Critical Illness, and Hospital ...

LexisNexis

Senior Data Scientist III

Raleigh, NC · On-site

$115K - $192K/yr

You will work closely with other data scientists and engineers to design, develop, and deploy ... Short-and-Long Term Disability, Life and Accidental Death Insurance, Critical Illness, and Hospital ...

LexisNexis

Senior Data Scientist III

Raleigh, NC · On-site +1

$115K - $192K/yr

You will work closely with other data scientists and engineers to design, develop, and deploy ... Short-and-Long Term Disability, Life and Accidental Death Insurance, Critical Illness, and Hospital ...

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Showing results 1-20

All JobsInsurance Data Engineer JobsInsurance Data Engineer Jobs in Raleigh, NC

Insurance Data Engineer information

See Raleigh, NC salary details

$43.3K

$126.1K

$172.5K

How much do insurance data engineer jobs pay per year?

As of Jul 16, 2026, the average yearly pay for insurance data engineer in Raleigh, NC is $126,095.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,300.00 and $133,700.00 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 are popular job titles related to Insurance Data Engineer jobs in Raleigh, NC? For Insurance Data Engineer jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Insurance Data Engineer jobs in Raleigh, NC look for? The top searched job categories for Insurance Data Engineer jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Insurance Data Engineer jobs? Cities near Raleigh, NC with the most Insurance Data Engineer job openings:
Insurance Data Engineer jobs near you
Infographic showing various Insurance Data Engineer job openings in Raleigh, NC as of July 2026, with employment types broken down into 77% Full Time, and 23% Contract. Highlights an 80% In-person, 14% Hybrid, and 6% Remote job distribution, with an average salary of $126,095 per year, or $60.6 per hour.
Lead Software Developer Engineer in Test, StorageGRID

Lead Software Developer Engineer in Test, StorageGRID

NetApp

Morrisville, NC • On-site, Remote

Other

Medical, Life, Retirement, PTO

Posted 3 days ago

Job description

Job Summary

NetApp is pioneering the development of StorageGRID object storage - AWS cloud compatible software powering the exponential growth in AI data lakes. As a Software Developer Engineer in Test, this is your chance to work alongside a group of talented developers, impart your vision, and rapidly launch the latest cloud storage software. Your incredible testing and automation skills will create opportunities to contribute clean code. Naturally, you are as comfortable solving our customer's AI data lake challenges by writing new code as you are improving productivity by refactoring. You are opinionated while flexible and know when to adopt new technologies. 

We are true believers of Agile development and have been on the journey for many years. Since you maintain supreme levels of communication with your peers, we won't inundate you with process and documentation as you work in our flexible hybrid work-from-home/office model. 

Throughout the world, leading organizations count on NetApp to manage and store their data. From the edge of human endurance in Formula One auto racing to the edge of the universe with CERN's Large Hadron Collider, we help our customers do things they couldn't before-at speeds you never thought possible. 

Role Overview 

In this role, you will serve as a key technical leader and force multiplier for our established, high-performing Software Quality team. Your deep passion for software quality will drive meaningful improvements: introducing effective processes, tools, and technologies; mentoring engineers to strengthen their test design and automation skills; and guiding the team's progression from primarily functional testing to addressing sophisticated challenges such as race conditions, scalability, stability, and performance in distributed systems.

Job Responsibilities
  • Own and drive end-to-end system test strategy, defining coverage aligned to customer workflows and risk areas. 
  • Design and implement scalable regression frameworks with parallel execution and smart test selection. 
  • Leverage AI/GenAI for test case generation, including boundary, edge, and failure scenarios. 
  • Build AI-assisted and self-healing automation frameworks to reduce maintenance and improve resilience. 
  • Apply LLMs for test design, validation, debugging, and defect analysis. 
  • Use AI techniques for anomaly detection, log analysis, and failure triaging. 
  • Enable AI-driven synthetic test data generation for complex distributed workflows. 
  • Drive root-cause analysis using AI-assisted insights and data-driven debugging approaches. 
  • Integrate AI into CI/CD pipelines to improve feedback cycles and regression efficiency. 
  • Mentor engineers on AI-driven testing strategies and modern QA practices. 
Job Requirements
  • Proven experience in system-level testing and automation frameworks. 
  • Strong technical foundation in distributed systems, cloud APIs, and Linux environments. 
  • Expertise in scripting languages such as Python or Ruby. 
  • Hands-on experience applying AI/ML techniques to software testing workflows. 
  • Experience with LLM-based tools for test generation, debugging, and validation. 
  • Ability to design AI-driven quality engineering solutions and frameworks. 
  • Familiarity with Agile development, CI/CD, and Test-Driven Development (TDD). 
  • Preferred Skills 
  • Experience testing large-scale distributed storage systems or complex enterprise platforms. 
  • Hands-on experience with AI-assisted testing, including test case generation and automation. 
  • Experience with prompt engineering for structured and reproducible test generation. 
  • Understanding of AI-specific failure patterns such as hallucinations and non-deterministic outputs. 
  • Ability to design guardrails and validation layers for AI-generated outputs. 
  • Experience with intelligent test prioritization and selection using ML techniques. 
  • Familiarity with agentic workflows and autonomous testing systems. 
  • Experience integrating AI into CI/CD pipelines for automated validation. 
  • Knowledge of synthetic data generation and data engineering for testing systems. 
  • Education & Experience 
  • A minimum of 10 years of experience is required. A Bachelor's or Master's degree in Computer Science, Engineering, or equivalent experience. 

Compensation:
The target salary range for this position is 170,000 - 253,000 USD. The salary offered will be determined by the candidate's location, qualifications, experience, and education and may be outside of this range. The range is based on 'On Target Earnings' (OTE) representing the total potential earnings, which is the sum of the base salary and potential commission earned when performance targets are achieved. Final compensation packages are competitive and in line with industry standards, reflecting a variety of factors, and include a comprehensive benefits package. This may cover Health Insurance, Life Insurance, Retirement or Pension Plans, Paid Time Off, various Leave options, employee stock purchase plan, and/or restricted stocks (RSU's). These offerings are subject to regional variations and governed by local laws, regulations, and company policies. We will provide detailed information about the specific benefits for your region during the recruitment process.

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