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Insurance Data Engineer Jobs in Phoenix, AZ (NOW HIRING)

Vultus Inc

Data Engineer

Phoenix, AZ · On-site

$113K - $136K/yr

Data Engineer Location Hyderabad, India (Hybrid) Employment Type Full-Time Experience 3-7 Years ... Health insurance * Performance bonus * Flexible work environment * Learning and certification ...

Kimley-Horn

Data Engineer

Phoenix, AZ · On-site

$104K - $125K/yr

Overview We are seeking a Data Engineer to join our growing Data & Analytics team. This role is ... Low-cost medical, dental, and vision insurance options. * Time Off: Personal leave, flexible ...

Kimley-Horn

Data Engineer

Phoenix, AZ

$113K - $136K/yr

Overview We are seeking a Data Engineer to join our growing Data & Analytics team. This role is ... Low-cost medical, dental, and vision insurance options. * Time Off: Personal leave, flexible ...

Kimley-Horn

Data Engineer

Phoenix, AZ

$113K - $136K/yr

Overview We are seeking a Data Engineer to join our growing Data & Analytics team. This role is ... Low-cost medical, dental, and vision insurance options. * Time Off: Personal leave, flexible ...

Kimley-Horn

Data Engineer

Phoenix, AZ

$104K - $125K/yr

We are seeking a Data Engineer to join our growing Data & Analytics team. This role is responsible ... Low-cost medical, dental, and vision insurance options. * Time Off: Personal leave, flexible ...

EXL Service

Principle Data Engineer

Phoenix, AZ · On-site

$113K - $136K/yr

Insurance, Health, Analytics, and Emerging businesses. Required Skills: Python, Pyspark/Spark, SQL, Data Lake (ON Prem or cloud) AWS, Snowflake. Job Summary: The Data Engineer's role is to play a ...

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All JobsInsurance Data Engineer JobsInsurance Data Engineer Jobs in Phoenix, AZ

Insurance Data Engineer information

See Phoenix, AZ salary details

$44.2K

$128.8K

$176.2K

How much do insurance data engineer jobs pay per year?

As of Jul 25, 2026, the average yearly pay for insurance data engineer in Phoenix, AZ is $128,797.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,700.00 and $136,500.00 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 Phoenix, AZ? For Insurance Data Engineer jobs in Phoenix, AZ, the most frequently searched job titles are:
What job categories do people searching Insurance Data Engineer jobs in Phoenix, AZ look for? The top searched job categories for Insurance Data Engineer jobs in Phoenix, AZ are:
What cities near Phoenix, AZ are hiring for Insurance Data Engineer jobs? Cities near Phoenix, AZ with the most Insurance Data Engineer job openings:
Insurance Data Engineer jobs near you
Infographic showing various Insurance Data Engineer job openings in Phoenix, AZ as of July 2026, with employment types broken down into 50% Full Time, and 50% Part Time. Highlights an 50% In-person, and 50% Remote job distribution, with an average salary of $128,797 per year, or $61.9 per hour.
Data Engineer

Data Engineer

Vultus Inc

Phoenix, AZ • On-site

$113K - $136K/yr

Full-time

Medical, PTO

Posted 16 days ago

Job description

Data Engineer

Location

Hyderabad, India (Hybrid)

Employment Type

Full-Time

Experience

3–7 Years

Salary

₹8 LPA – ₹18 LPA (Based on experience and skills)

Job Summary

We are looking for a skilled Data Engineer to design, build, and maintain scalable data pipelines and data infrastructure. The ideal candidate should have experience working with large datasets, cloud platforms, ETL processes, and data warehousing solutions. You will collaborate with data analysts, data scientists, and software engineers to ensure reliable and efficient data processing.

Key Responsibilities
  • Design, develop, and maintain scalable ETL/ELT pipelines.
  • Build and optimize data models and data warehouses.
  • Integrate data from multiple sources into centralized repositories.
  • Ensure data quality, consistency, and governance.
  • Optimize SQL queries and improve data processing performance.
  • Work with cloud-based data platforms and big data technologies.
  • Monitor, troubleshoot, and resolve data pipeline issues.
  • Collaborate with cross-functional teams to support business intelligence and analytics.
  • Implement data security and compliance best practices.
  • Document data architecture and technical processes.
Primary Skills
  • Python
  • SQL
  • Apache Spark
  • Apache Kafka
  • ETL/ELT Development
  • Data Warehousing
  • Snowflake
  • Apache Airflow
  • Azure Data Factory (ADF)
  • AWS Glue
  • Databricks
  • Git
Secondary Skills
  • Hadoop Ecosystem
  • Docker
  • Kubernetes
  • Terraform
  • Power BI
  • Tableau
  • Linux
  • CI/CD Pipelines
  • REST APIs
  • Data Governance
Required Qualifications
  • Bachelor's degree in Computer Science, Information Technology, or a related field.
  • 3–7 years of experience in Data Engineering.
  • Strong programming skills in Python and SQL.
  • Experience with cloud platforms such as AWS, Azure, or GCP.
  • Hands-on experience with ETL tools and data pipelines.
  • Strong understanding of relational and NoSQL databases.
  • Knowledge of distributed data processing frameworks.
Preferred Qualifications
  • Experience with Databricks or Snowflake.
  • Cloud certifications (AWS, Azure, or GCP).
  • Experience with streaming platforms like Kafka.
  • Knowledge of DevOps and Infrastructure as Code.
Soft Skills
  • Excellent analytical and problem-solving skills.
  • Strong communication and collaboration abilities.
  • Ability to work in Agile environments.
  • Good time management and organizational skills.
  • Quick learner with a proactive attitude.
Benefits
  • Competitive salary package
  • Health insurance
  • Performance bonus
  • Flexible work environment
  • Learning and certification support
  • Paid leave and holidays
  • Career growth opportunities
  • Employee wellness programs