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Insurance Data Engineer Jobs in Milwaukee, WI (NOW HIRING)

MAXIMUS

Senior Engineer - Data Analytics

Milwaukee, WI · On-site

$104K - $141K/yr

... data and semantic model design. - Analyze requirements and apply architectural and engineering ... Additionally, Maximus provides a variety of benefits to employees, including health insurance ...

Komatsu

Director, AI and Data

Milwaukee, WI · On-site

$193K - $250K/yr

Build, lead, and develop a high-performing team of data scientists, engineers, and analytics ... Life insurance * Employee learning and development programs Diversity & Inclusion Commitment At ...

Sun Life

Data & Reporting Business Analyst

Milwaukee, WI · On-site

$60K - $90K/yr

Proficiency with at least one programming language (Python, R, or similar) * Experience building ... Insurance and claims operations business acumen * Understanding of inventory management and demand ...

Trace-A-Matic

Manufacturing Engineer

Brookfield, WI

$33.17 - $48.08/hr

Medical, Dental, Vision Insurance * 401k with company contribution * Exciting, fast-paced ... data (engineering drawings, specifications, purchase orders, etc.) and create shop routings ...

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Showing results 1-20

All JobsInsurance Data Engineer JobsInsurance Data Engineer Jobs in Milwaukee, WI

Insurance Data Engineer information

See Milwaukee, WI salary details

$43.8K

$127.8K

$174.9K

How much do insurance data engineer jobs pay per year?

As of Jul 7, 2026, the average yearly pay for insurance data engineer in Milwaukee, WI is $127,802.00, according to ZipRecruiter salary data. Most workers in this role earn between $112,800.00 and $135,500.00 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 Milwaukee, WI? For Insurance Data Engineer jobs in Milwaukee, WI, the most frequently searched job titles are:
What job categories do people searching Insurance Data Engineer jobs in Milwaukee, WI look for? The top searched job categories for Insurance Data Engineer jobs in Milwaukee, WI are:
What cities near Milwaukee, WI are hiring for Insurance Data Engineer jobs? Cities near Milwaukee, WI with the most Insurance Data Engineer job openings:
Insurance Data Engineer jobs near you
Infographic showing various Insurance Data Engineer job openings in Milwaukee, WI as of July 2026, with employment types broken down into 78% Full Time, and 22% Contract. Highlights an 80% In-person, 14% Hybrid, and 6% Remote job distribution, with an average salary of $127,802 per year, or $61.4 per hour.
Senior Engineer - Data Analytics

Senior Engineer - Data Analytics

MAXIMUS

Milwaukee, WI • On-site

$104K - $141K/yr

Other

Medical, Life, Retirement, PTO

Posted 4 days ago

Maximus rating

6.9

Company rating: 6.9 out of 10

Based on 292 frontline employees who took The Breakroom Quiz

243rd of 437 rated business services

Job description

Essential Duties and Responsibilities:
- Responsible for delivery of business intelligence (BI) information to the entire organization, including the assessment of business requirements, collection and identification of technical specifications, and the subsequent development of technology solutions.
- Develop and maintain data integration solutions (including ETL/ELT design and architecture), semantic layer objects, presentation objects, reports, and dashboards for delivery of analytic solutions.
- Translate business needs and requirements to system requirements, data mapping, and data and semantic model design.
- Analyze requirements and apply architectural and engineering concepts to develop solutions that meet business needs while maintaining sustainability objectives, including: scalability, maintainability, security, reliability, extensibility, flexibility, availability, and manageability.
- Provide training and consulting for various technical and non-technical internal teams.
- Produce work breakdowns and task estimates (scoping and tracking activities).
- Produce and document standard and best practices.
- Provide level 3 support for production systems.
Job-Specific Essential Duties and Responsibilities:
- Working with the Data Architect and senior leadership to execute on data model designs and enterprise solutions.
- Expertly communicate relevant and timely information that drives consensus, improves solutions and fosters teamwork between senior leadership, coworkers and internal Maximus clients that drives good project outcomes and solution delivery.
- Takes ownership of solutions and develops broad subject matter expertise of our underlying data.
- Adhere to SDLC best practices, and assist in overall promotion to prod effort around data validation and completeness of solution and delivery.
Minimum Requirements
- Bachelor's degree (Master's preferred) in Computer Science, Data Science, Engineering, Information Systems, Mathematics, Statistics, or related field. Equivalent experience will be considered in lieu of a degree.
- 5+ years of experience in a technical role engineering data and/or analytics solutions.
- Proven track record of successfully delivering large data-centric projects.
- Ability to produce high quality documentation of business and system requirements, system design, data architecture, and training materials.
- Expert data skills, including complex queries, performance tuning, expertise in a variety of approaches (e.g., relational, dimensional, unstructured).
- Highly skilled in building data and semantic layers utilizing enterprise analytic tools such as Tableau, Microstrategy or PowerBI.
EEO Statement
Maximus is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, age, national origin, disability, veteran status, genetic information and other legally protected characteristics.
Pay Transparency
Maximus compensation is based on various factors including but not limited to job location, a candidate's education, training, experience, expected quality and quantity of work, required travel (if any), external market and internal value analysis including seniority and merit systems, as well as internal pay alignment. Annual salary is just one component of Maximus's total compensation package. Other rewards may include short- and long-term incentives as well as program-specific awards. Additionally, Maximus provides a variety of benefits to employees, including health insurance coverage, life and disability insurance, a retirement savings plan, paid holidays and paid time off. Compensation ranges may differ based on contract value but will be commensurate with job duties and relevant work experience. An applicant's salary history will not be used in determining compensation. Maximus will comply with regulatory minimum wage rates and exempt salary thresholds in all instances.
Accommodations
Maximus provides reasonable accommodations to individuals requiring assistance during any phase of the employment process due to a disability, medical condition, or physical or mental impairment. If you require assistance at any stage of the employment process-including accessing job postings, completing assessments, or participating in interviews,-please contact People Operations at applicantaccom@maximus.com.
Minimum Salary
$
115,000.00
Maximum Salary
$
135,000.00

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