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Insurance Data Processing Jobs in Michigan (NOW HIRING)

Auto-Owners Insurance

Data Specialist

Lansing, MI · On-site

Auto-Owners Insurance, a top-rated insurance carrier, is seeking a motivated Data Specialist to join our team. The position analyzes data processes and the needs of users and stakeholders; develops ...

E*Pro, Inc.

ETL Architect

Grand Rapids, MI · On-site

Insurance data model experience, such as IAA and Accord. * Strong knowledge and extensive practical ... ETL processes Additional Information If you are interested, please send across your resume to ...

Advantasure, Inc.

Actuarial Consultant

Detroit, MI · On-site

Ensure completeness, accuracy and appropriateness of all insurance data used in the production of ... Drive key department processes. May provide technical guidance to and coordinate work less ...

CSAA

In order for your application to be correctly processed please sign-in before you apply Internal ... Job Title Senior Data Science Consultant, Insurance - Remote Requisition Number R7828 Senior Data ...

AAA Life Insurance Company

Data Analyst III

Livonia, MI · On-site

$90 - $120/hr

... Life Insurance makes effective business and operational decisions. As a Data Analyst, you will be ... Develop and implement data governance and quality assurance processes. * Create and maintain Power ...

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Insurance Data Processing information

What is insurance data processing?

Insurance Data Processing refers to the collection, entry, management, and analysis of data related to insurance policies, claims, customers, and transactions. Professionals in this field use specialized software and systems to ensure that insurance information is accurate, up-to-date, and secure. Their work supports the smooth operation of insurance companies by helping to process claims, issue policies, and generate reports for decision-making. Accuracy and attention to detail are crucial in this role due to the sensitive nature of insurance data.

What are the key skills and qualifications needed to thrive as an insurance data processing specialist?

To thrive as an Insurance Data Processing Specialist, you need strong attention to detail, proficiency in data entry, and a solid understanding of insurance terminology, typically supported by a high school diploma or relevant associate degree. Familiarity with insurance management software, claims processing systems, and database tools such as Microsoft Excel is commonly required. Excellent organizational skills, problem-solving abilities, and effective communication help you excel in managing large volumes of sensitive information. These skills ensure accuracy, minimize errors, and support efficient operations within insurance organizations.

What are some common challenges faced in an insurance data processing role and how can they be addressed?

One of the main challenges in Insurance Data Processing is managing large volumes of sensitive data accurately and efficiently, especially when dealing with tight deadlines and evolving regulatory requirements. Errors in data entry or processing can impact claims or policy management, making attention to detail and strong organizational skills essential. To address these challenges, many teams rely on robust data management software, regular training, and collaborative workflows to ensure accuracy and compliance. Proactively seeking feedback and staying updated on industry best practices can also help professionals excel in this role.

What is the difference between Insurance Data Processing vs Insurance Claims Processing?

AspectInsurance Data ProcessingInsurance Claims Processing
Required CredentialsTypically high school diploma or equivalent; some roles may require certifications in data managementHigh school diploma or equivalent; often requires knowledge of claims procedures and insurance policies
Work EnvironmentOffice setting, working with databases and data entry systemsOffice environment, interacting with claim documents and insurance systems
Employer & Industry UsageInsurance companies, third-party administrators, data service providersInsurance companies, claims adjusters, third-party claims processors

Insurance Data Processing involves managing and organizing insurance-related data, focusing on data accuracy and database management. Insurance Claims Processing centers on evaluating and processing insurance claims submitted by policyholders, ensuring proper documentation and compliance. While both roles support insurance operations, Data Processing emphasizes data management, whereas Claims Processing focuses on claim evaluation and settlement.

What are popular job titles related to Insurance Data Processing jobs in Michigan?

For Insurance Data Processing jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Insurance Data Processing jobs in Michigan look for?

The top searched job categories for Insurance Data Processing jobs in Michigan are:

What cities in Michigan are hiring for Insurance Data Processing jobs?

Cities in Michigan with the most Insurance Data Processing job openings:

Insurance Data Processing jobs near you

Senior Full-Stack BI Architect / Fabric Data Engineer

Proactive Technology Management

Ferndale, MI • On-site

$62.50 - $83.75/hr

Full-time

Medical, Dental, Vision, Retirement

Re-posted 7 days ago

Job description

About Us

At Proactive Technology Management, we're transforming how businesses harness data to drive innovation and informed decision-making. As leaders in the SMB space, we leverage cutting-edge technologies to deliver actionable insights that give our clients a competitive advantage. We're seeking a Senior Full-Stack BI Architect / Fabric Data Engineer to design and implement innovative, domain-driven data solutions that humanize data and empower decision-makers. If you have a passion for making data meaningful and impactful, we want to hear from you!

Role Summary

As a Senior Full-Stack BI Architect / Fabric Data Engineer, you will lead the design and development of robust, enterprise-grade data solutions that prioritize human-centric design through the use of ubiquitous language and domain-driven principles. You will leverage deep expertise in medallion architecture, advanced data modeling, and visualization to ensure our clients receive intuitive, actionable insights. Your technical expertise in the Microsoft Cloud Data Stack, DAX, Power Query M, SQL, and Spark Python will drive success in building scalable, user-friendly solutions.

Key Responsibilities
  • Lead the design and implementation of ETL/ELT pipelines within a medallion architecture (Bronze, Silver, and Gold layers) to ensure data quality, scalability, and accessibility across use cases.
  • Architect and develop advanced data models that reflect domain-driven design principles, aligning with business domains and using ubiquitous language to ensure clarity and usability for all stakeholders.
  • Design and implement star and snowflake schemas, along with medallion schema practices, to provide flexible, high-performance data structures for analytics.
  • Create dynamic, user-centric dashboards and advanced reports in Power BI, empowering stakeholders with real-time insights and actionable metrics.
  • Leverage DAX and Power Query M to craft sophisticated calculations and transformations that enhance data usability and business relevance.
  • Build and optimize SQL-based solutions for database management, queries, and data integration, ensuring efficiency and scalability.
  • Use Spark Python for processing large datasets and performing advanced analytics to meet complex business requirements.
  • Collaborate with business leaders and cross-functional teams to understand data needs, define key performance indicators (KPIs), and ensure alignment with organizational goals.
  • Stay informed on advancements in data engineering, business intelligence, and analytics, continuously driving innovation and improvement.
  • Mentor team members to build organizational capacity in BI and data engineering best practices.

Requirements

Qualifications
  • Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field; advanced certifications in data engineering or BI are a plus.
  • 7+ years of experience in data engineering, BI architecture, or a related role, with a focus on enterprise-grade solutions.
  • In-depth expertise in medallion architecture, data modeling (star schemas, snowflake schemas), and best practices for data warehousing.
  • Proven ability to implement domain-driven design (DDD) principles, ensuring data solutions reflect business domains and are accessible through ubiquitous language.
  • Expert-level proficiency in Power BI, DAX, Power Query M, and SQL, with demonstrated success delivering scalable, impactful BI solutions.
  • Strong programming skills with Spark Python for advanced data processing and analytics.
  • Experience with the Microsoft Cloud Data Stack (Azure Data Factory, Azure Synapse Analytics, Microsoft Fabric) and other cloud technologies.
  • A track record of translating complex datasets into intuitive insights, creating value for both technical and non-technical stakeholders.
  • Exceptional problem-solving skills, attention to detail, and ability to thrive in a fast-paced, dynamic environment.
  • Strong communication and leadership skills, with a focus on collaboration and stakeholder engagement.

Benefits

  • Competitive compensation tailored to senior-level expertise.
  • Opportunities to shape data strategy and lead transformative BI projects.
  • Ongoing professional development through advanced training and certifications.
  • A supportive, innovative culture that values diversity, inclusion, and creativity.
  • Flexible remote work arrangements to support work-life balance.
  • Comprehensive health, dental, and vision insurance
  • 401(k) retirement plan with company match

If you're ready to lead the next evolution of business intelligence—harnessing the power of medallion architecture, domain-driven design, and user-centric modeling—apply today. Help us transform data into a powerful, humanized tool for business success.