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Insurance Data Engineer Jobs in Arizona (NOW HIRING)

Staffingine LLC

AI ML Engineer

Phoenix, AZ · On-site

$113K - $136K/yr

Data Engineering ETL processes data wrangling and feature engineering * Insurance Reinsurance Domain Knowledge Exposure to actuarial models risk assessment and claims analytics Technical Skills: * R ...

TEKsystems

Data Center Design Engineer

Chandler, AZ · Hybrid

$60.53/hr

Data Center Design Engineer Chandler, AZ Hybrid (3 Days in 2 Days remote) 12-24 Month Contract ... Insurance (Voluntary Life & AD&D for the employee and dependents) • Short and long-term ...

Master Electronics

Data Scientist II

Phoenix, AZ · On-site

Partner with software engineers, data engineers, product managers, and subject-matter experts ... World-class and affordable insurance plans ensure you and your family stay healthy Secure Your ...

Master Electronics

Data Scientist II

Phoenix, AZ · On-site

Partner with software engineers, data engineers, product managers, and subject-matter experts ... World-class and affordable insurance plans ensure you and your family stay healthy Secure Your ...

Master Electronics

Data Scientist II

Phoenix, AZ · On-site

Partner with software engineers, data engineers, product managers, and subject-matter experts ... World-class and affordable insurance plans ensure you and your family stay healthy Secure Your ...

Oscar Health

Associate, Process Improvement

Tempe, AZ · Hybrid

$87K - $114K/yr

A bachelor's degree or 3+ years commensurate experience * 3+ years of work experience in operations, health insurance, data analysis, engineering and/or consulting * 2+ years of experience using data ...

Ascend Learning

Director Data & AI

Gilbert, AZ · On-site +1

Align data engineering capacity through a blended in-house and MSP model; partner with the Director ... Company paid life Insurance * 401(k) with company match * Paid time off and parental leave

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Insurance Data Engineer information

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.

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 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.

What are popular job titles related to Insurance Data Engineer jobs in Arizona?

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

What job categories do people searching Insurance Data Engineer jobs in Arizona look for?

The top searched job categories for Insurance Data Engineer jobs in Arizona are:

What cities in Arizona are hiring for Insurance Data Engineer jobs?

Cities in Arizona with the most Insurance Data Engineer job openings:

Insurance Data Engineer jobs near you
Infographic showing various Insurance Data Engineer job openings in Arizona as of September 2026, with employment types broken down into 100% Full Time. Highlights an 74% In-person, and 26% Hybrid job distribution.

AI ML Engineer

Phoenix, AZ • On-site

Staffingine LLC
Recruiting and Staffing Services • 51 - 200 employees
Learn more about Staffingine LLCexternal

$113K - $136K/yr

Contractor

Re-posted 22 days ago

Job description

Job Title: AI ML Engineer
Job Location: Charlotte, NC / Phoenix, AZ
Job Type: Contract

Job Description:

  • Programming Languages Python Pandas NumPy Scikitlearn SQL
  • Statistical Modeling Machine Learning Regression Classification Clustering Time Series Forecasting
  • Data Visualization Power BI Tableau Matplotlib Seaborn
  • Big Data Technologies Spark Hadoop basic understanding
  • Cloud Platforms Azure or AWS especially for data pipelines and model deployment
  • Data Engineering ETL processes data wrangling and feature engineering
  • Insurance Reinsurance Domain Knowledge Exposure to actuarial models risk assessment and claims analytics

Technical Skills:

  • R or SAS for statistical analysis
  • Experience with Natural Language Processing NLP
  • Familiarity with geospatial data and mapping tools
  • Knowledge of Monte Carlo simulations and stochastic modeling
  • Experience with Git and CICD pipelines
  • Exposure to regulatory frameworks Solvency II IFRS 17

Soft Skills:

  • Strong problem solving and critical thinking abilities
  • Excellent communication and storytelling skills for nontechnical stakeholders
  • Collaborative mindset with cross functional teams actuarial underwriting IT
  • Ability to manage multiple projects and prioritize effectively
  • Curiosity and continuous learning attitude
  • High attention to detail and data integrity

Qualifying Questions:

  • Can you describe a project where you applied machine learning to solve a business problem in the insurance or financial domain
  • How do you ensure the quality and reliability of your data before building models
  • Have you worked with actuarial teams or underwriting departments before If yes how did you contribute to their decision making process

Mandatory Skills : AI/GenAI Research