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Insurance Data Processing Jobs in Michigan (NOW HIRING)

Senior Data Engineer

Detroit, MI ยท On-site

$97K - $131K/yr

Knowledge of the insurance business data domain is a major plus, including familiarity with insurance data concepts, business processes, and analytics use cases. * Ability to design trusted ...

New

Drive migration of legacy insurance data systems to CDA platform, overseeing data profiling ... Proficiency in SQL and large-scale data processing. Qualification And Education: * Strong knowledge ...

Senior Python Data Engineer

Atlanta, MI ยท On-site

$100K - $114K/yr

Design, build, and optimize data ingestion, transformation, and processing pipelines using modern ... Medical/Dental/Vision/Life Insurance. * Paid holidays plus Paid Time Off. * 401(k) plan and ...

New

Data Architect

East Lansing, MI ยท On-site

$105K - $143K/yr

Lead the migration from legacy batch processes to automated, event-driven, or CDC-based ingestion ... Experience in the insurance industry, preferred. * Snowflake certification, a plus. * Familiarity ...

Data Engineer

Detroit, MI ยท On-site

$130K - $150K/yr

... data processing technologies Expertise with Microsoft Azure infrastructure and data resources ... and services, banking, insurance and public administration sectors in the definition and ...

Data Engineer

Detroit, MI ยท On-site

$130K - $150K/yr

... processing technologies * Expertise with Microsoft Azure infrastructure and data resources ... and services, banking, insurance and public administration sectors in the definition and ...

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Showing results 1-20

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 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:

Senior Data Engineer

Detroit, MI โ€ข On-site

Brooksource
IT Servicesย โ€ขย 501 - 1,000 employees

$97K - $131K/yr

Other

Medical, Dental, Vision, Retirement, PTO

Posted yesterday

New


Job description

Are you passionate about data, architecture, software development, and analytics? Do you bring deep experience with cloud technologies, data warehousing, data integration, data modeling, and API development? Do you believe in modern engineering practices, collaboration, and innovation to build the next generation of enterprise data and AI platforms? If so, weโ€™d like to talk with you.

We are seeking a Manager Data Engineer / Principal Data Engineer to help design, build, and evolve modern data solutions within our Enterprise Data and AI organization. This role is ideal for a strong technical leader with handsโ€‘on experience delivering cloudโ€‘based data platforms, scalable data pipelines, and enterprise data solutions that support analytics, reporting, data science, and AI use cases.

The ideal candidate will bring experience implementing data lakes, cloud data warehouses, and modern data engineering solutions, including data ingestion, transformation, standardization, preparation, data quality management, and structured and unstructured data processing. This role also requires experience with relational and NoSQL data technologies, largeโ€‘scale data integration, API development, and enterprise data modeling, including Data Vault.

Experience with modern cloud data platform technologies, data architecture, and software engineering practices is essential. Knowledge of AI/ML, data science, and LLMโ€‘related use cases is also a plus. Knowledge of the insurance business data domain is a significant advantage, particularly in supporting solutions that enable Insurance Data and Analytics capabilities. This role will be responsible for creating, maintaining, and optimizing enterprise data pipelines and related processes that support strategic analytics, machine learning, and AIโ€‘driven business capabilities across Insurance line of business.

The selected candidate will help build and advance critical platform capabilities, including Insurance Data and Analytics solutions, data ingestion and transformation frameworks, governanceโ€‘aligned data engineering processes, and trusted data foundations for analytics and AI. The ideal candidate will bring proven experience leading cloud data engineering initiatives, driving scalable solution design, and establishing strong engineering standards across complex enterprise environments.

The Work Itself

  • Lead and manage the Data Engineering squad, focusing on scalable platforms and engineer growth.
  • Design, build, and optimize modern data pipelines and enterprise data solutions that support analytics, reporting, data science, and AI use cases.
  • Develop and implement cloudโ€‘based data engineering solutions, including data lakes, cloud data warehouses, and enterprise data platforms.
  • Design scalable data structures and support enterprise data storage using Data Vault modeling to enable flexible, auditable, and resilient data solutions.
  • Build and support data ingestion, transformation, preparation, and quality processes across structured and unstructured data sources.
  • Develop robust solutions for largeโ€‘scale data integration, relational and NoSQL data processing, and APIโ€‘based data services.
  • Enable trusted, highโ€‘quality, and accessible data for analytics, machine learning, and AIโ€‘driven business capabilities.
  • Partner with business and technology teams to define data requirements, transformation rules, integration needs, and solution designs that align to enterprise and lineโ€‘ofโ€‘business priorities.
  • Help advance Insurance Data and Analytics platform capabilities through scalable engineering, strong data foundations, and governanceโ€‘aligned practices.
  • Establish and maintain data quality, validation, monitoring, metadata, and lineage processes to support reliable and wellโ€‘managed enterprise data assets.
  • Apply modern software engineering methods and Agile practices to deliver scalable, reliable, and maintainable data solutions.
  • Promote engineering, operational, and design standards across data platforms and services.
  • Evaluate and recommend tools, technologies, and approaches that improve performance, delivery, and longโ€‘term supportability.
  • Collaborate across business and IT teams to solve complex technical challenges and deliver practical, scalable solutions.
  • Support enterprise data governance, data management, and data security requirements.
  • Provide technical leadership, mentor team members, and contribute to strong delivery outcomes through effective collaboration and sound engineering practices.

The Skills You Bring

  • Strong technical expertise in cloud data platforms and modern data engineering tools, combined with team leadership, strategic thinking, and crossโ€‘functional collaboration.
  • Bachelorโ€™s degree in computer science, Information Systems, or a related field; advanced degree preferred.
  • 8+ years of progressive experience in data engineering, including deep expertise in analyticsโ€‘focused data warehouse environments such as Snowflake.
  • Extensive handsโ€‘on experience designing and delivering cloudโ€‘based data solutions on AWS, including services such as S3, AWS CLI, Lambda, and DynamoDB.
  • Strong experience with modern data engineering and integration tools such as dbt, Qlik Replicate, InfoSphere DataStage, and CP4D.
  • Deep expertise in data modeling, including Data Vault, and in designing scalable, auditable, and resilient data structures that support enterprise analytics, reporting, and AI use cases.
  • Proven experience architecting and optimizing largeโ€‘scale data ingestion, transformation, cleansing, standardization, and deduplication processes across complex data environments.
  • Strong programming and automation skills in Python and other scripting languages used to support enterprise data engineering solutions.
  • Demonstrated experience leading the design and implementation of enterprise data pipelines using Git, DevOps practices, and modern software engineering approaches.
  • Strong background in largeโ€‘scale data integration, API development, and data migration across distributed systems and platforms.
  • Deep understanding of data governance, data management, metadata, lineage, and data security, with the ability to embed these practices into engineering solutions.
  • Proven ability to lead endโ€‘toโ€‘end solution delivery, working independently while providing technical direction across multiple initiatives and technologies.
  • Demonstrated success establishing and enforcing engineering, design, and operational standards across teams and platforms.
  • Ability to evaluate emerging tools, technologies, and architectural approaches, and recommend scalable solutions that improve performance, maintainability, and longโ€‘term supportability.
  • Proven ability to influence, advise, and partner effectively with senior business and technology stakeholders to identify strategic challenges, assess options, and recommend solutions.
  • Strong track record of mentoring engineers, promoting engineering excellence, and contributing to highโ€‘performing teams.
  • Extensive experience across the full software development lifecycle, including architecture, design, implementation, testing, deployment, and operational support.
  • Knowledge of the insurance business data domain is a major plus, including familiarity with insurance data concepts, business processes, and analytics use cases.
  • Ability to design trusted, highโ€‘quality data foundations that enable advanced analytics, machine learning, and AIโ€‘driven business capabilities.
  • Strong problemโ€‘solving, communication, and leadership skills, with the ability to translate complex technical concepts into practical business solutions.
  • Insurance Business data domain knowledge.

Why Join Us?

  • 401(k) Matching Plan
  • Relationship Driven Process to Find Your Best Fit
  • 6 Paid Holidays
  • Regular Meetings to Ensure Quality in Your Engagement

EEO Statement:

Brooksource is an equal opportunity employer that does not discriminate on the basis of actual or perceived race, color, creed, religion, national origin, ancestry, citizenship status, age, sex or gender (including pregnancy, childbirth, lactation and related medical conditions), gender identity or gender expression, sexual orientation, marital status, military service and veteran status, physical or mental disability, protected medical condition as defined by applicable state or local law, genetic information, or any other characteristic protected by applicable federal, state, or local laws and ordinances.

Brooksource offers competitive medical, dental, vision, Health Savings Account, Dependent Care FSA, and supplemental coverage with plans that can fit each employeeโ€™s needs. We offer a 401k plan that includes a company match and is fully vested after you become eligible, paid time off, sick time, and paid company holidays. We also offer an Employee Assistance Program (EAP) that provides services like virtual counseling, financial services, legal services, life coaching, etc.

Pay Disclaimer:

The pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.

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