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Insurance Data Processing Jobs in Connecticut (NOW HIRING)

Berkley

Data Engineer

Greenwich, CT · On-site

$128K - $154K/yr

Insurance and Reinsurance and Monoline Excess. Led by our Executive Chairman, founder and largest ... Familiarity with cloud data platforms and distributed processing frameworks (e.g., Databricks ...

Maximus

Data Coordination Analyst

Stamford, CT · On-site

... and recommend process improvements. This opportunity is well suited for a detail-oriented ... Additionally, Maximus provides a variety of benefits to employees, including health insurance ...

Maximus

Data Coordination Analyst

Hartford, CT · On-site

... and recommend process improvements. This opportunity is well suited for a detail-oriented ... Additionally, Maximus provides a variety of benefits to employees, including health insurance ...

Maximus

Data Coordination Analyst

Hamden, CT · On-site

... and recommend process improvements. This opportunity is well suited for a detail-oriented ... Additionally, Maximus provides a variety of benefits to employees, including health insurance ...

Maximus

Data Coordination Analyst

Bridgeport, CT · On-site

... and recommend process improvements. This opportunity is well suited for a detail-oriented ... Additionally, Maximus provides a variety of benefits to employees, including health insurance ...

Berkley

Data Engineer

Greenwich, CT · On-site

$128K - $154K/yr

Insurance and Reinsurance and Monoline Excess. Led by our Executive Chairman, founder and largest ... Familiarity with cloud data platforms and distributed processing frameworks (e.g., Databricks ...

Maximus

Data Coordination Analyst

Waterbury, CT · On-site

... and recommend process improvements. This opportunity is well suited for a detail-oriented ... Additionally, Maximus provides a variety of benefits to employees, including health insurance ...

Maximus

Data Coordination Analyst

New Haven, CT · On-site

... and recommend process improvements. This opportunity is well suited for a detail-oriented ... Additionally, Maximus provides a variety of benefits to employees, including health insurance ...

Maximus

Data Coordination Analyst

Norwalk, CT · On-site

... and recommend process improvements. This opportunity is well suited for a detail-oriented ... Additionally, Maximus provides a variety of benefits to employees, including health insurance ...

Maximus

Data Coordination Analyst

Danbury, CT · On-site

... and recommend process improvements. This opportunity is well suited for a detail-oriented ... Additionally, Maximus provides a variety of benefits to employees, including health insurance ...

Belcan

Project Data Analyst

Windsor, CT

$29 - $35/hr

Evaluate data pull processes and recommend/implement process improvements * Develop reporting ... Benefits offered MAY include health, dental, vision, and life insurance; 401(k); education ...

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Insurance Data Processing information

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 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, and why are they important?

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 popular job titles related to Insurance Data Processing jobs in Connecticut? For Insurance Data Processing jobs in Connecticut, the most frequently searched job titles are:
What job categories do people searching Insurance Data Processing jobs in Connecticut look for? The top searched job categories for Insurance Data Processing jobs in Connecticut are:
What cities in Connecticut are hiring for Insurance Data Processing jobs? Cities in Connecticut with the most Insurance Data Processing job openings:
Insurance Data Processing jobs near you
Data Engineer

Data Engineer

Berkley

Greenwich, CT • On-site

$128K - $154K/yr

Other

Re-posted 16 hours ago

Job description

Company Details
"Our Company provides a state of predictability which allows brokers and agents to act with confidence."
Founded in 1967, W. R. Berkley Corporation has grown from a small investment management firm into one of the largest commercial lines property and casualty insurers in the United States.
Along the way, we've been listed on the New York Stock Exchange, become a Fortune 500 Company, joined the S&P 500, and seen our gross written premiums exceed $10 billion.
Today the Berkley brand comprises more than 60+ businesses worldwide and is divided into two segments: Insurance and Reinsurance and Monoline Excess. Led by our Executive Chairman, founder and largest shareholder, William. R. Berkley and our President and Chief Executive Officer, W. Robert Berkley, Jr., W.R. Berkley Corporation is well-positioned to respond to opportunities for future growth.
The Company is an equal employment opportunity employer.
Responsibilities
We are seeking a Data Engineer with strong engineering, coding, and problem-solving skills to design, build, and operate data platforms that support actuaries, analytics, modeling, and AI-enabled workflows.
This role is suited to someone who is technically strong, comfortable working independently, and able to translate complexity into robust, well-designed systems that others can rely on.
The position emphasizes engineering rigor, high-quality code, system reliability, and sound judgment over one-off solutions or purely mechanical implementations.
We seek someone to challenge the status quo and find better ways to build and operate data systems. You will advocate for the thoughtful application of modern data engineering, data science, and AI approaches.
Responsibilities
  • Write production-quality code for data ingestion, transformation, orchestration, and monitoring.
  • Design, build, and maintain reliable, scalable data pipelines and data platforms, including batch or distributed processing workloads (e.g., Spark-based pipelines).
  • Partner with actuaries, analytics, data science, and business teams to enable modeling and AI uses.
  • Apply AI-assisted engineering approaches, including LLM-enabled tools or agents, to improve data quality, observability, documentation, and productivity.
  • Identify data quality issues, bottlenecks, and failure modes; design systems that are resilient and observable.
  • Stay current with data engineering and AI platform advancements, evaluate new tools, and recommend adoption where appropriate.
  • Apply professional skepticism and alternate approaches to validate data correctness, lineage, and assumptions.
  • Communicate system design, trade-offs, and limitations clearly to technical and non-technical stakeholders.
  • Provide support and guidance to others who are at earlier stages in their data engineering or AI journey.

Qualifications
  • 4-7 years of relevant data engineering, software engineering, or technical experience. A Master's degree in Data Engineering or Computer Science.
  • Familiarity with cloud data platforms and distributed processing frameworks (e.g., Databricks, Snowflake, Spark, or similar), and modern data engineering tooling.
  • Strong programming skills, particularly in Python and SQL (including experience with distributed or batch processing frameworks such as PySpark or equivalent), with an emphasis on maintainable, testable code.
  • Experience designing and operating data pipelines, data lakes/warehouses, or distributed data systems.
  • Experience applying AI, machine learning, or LLM-based tools to real engineering problems (e.g., building agents, calling model APIs, integrating AI into engineering workflows).
  • Experience working with large or complex data flows and creating defensible system designs and implementation plans.
  • Strong professional judgment, curiosity, and attention to detail.

Sponsorship Details
Sponsorship not Offered for this Role

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