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Insurance Data Processing Jobs in Connecticut (NOW HIRING)

Berkley

Data Engineer

Greenwich, CT

$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 ...

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 ...

W. R. Berkley Corporation

Data Engineer

Greenwich, CT · On-site

$128K - $154K/yr

Berkley Corporation is one of the largest commercial lines property and casualty insurers in the ... processing workloads (e.g., Spark‑based pipelines). • Partner with actuaries, analytics, data ...

Munich Re

Data Scientist

Hartford, CT · On-site

... the insurance industry or 4+ years predictive analytics, data mining or statistical analysis in ... Proficiency with natural language processing (NLP) techniques and tools for extracting insights ...

CYNET SYSTEMS

Data Entry Operator

Shelton, CT · On-site

$19 - $24/hr

Sorts and processes requisitions. Skills: * Data Entry. * Numerical Data Input. * Alphabetical Data ... Medical, Dental, and Vision Insurance * 401(k) Retirement Plan * Health Savings Account (HSA)

New

CYNET SYSTEMS

Data Entry Operator

Shelton, CT · On-site

$19 - $24/hr

Sorts and processes requisitions. Skills: Data Entry. Numerical Data Input. Alphabetical Data Input ... Medical, Dental, and Vision Insurance 401(k) Retirement Plan Health Savings Account (HSA ...

New

Synectics

Data Entry Operator

Shelton, CT · On-site

* Inputs various data into specified computer system with limited judgment. * Under direct ... processes requisitions. * Shift/Time Zone: 8:30 am to 5:00 pm Benefits: Healthcare Insurance:

Randstad Digital

Data Architect

Hartford, CT · On-site

$65 - $70/hr

... process meets the needs of all applicants. If you require a reasonable accommodation to make your ... life insurance offerings, short-term disability, and a 401K plan (all benefits are based on ...

Linde

Data Scientist

Danbury, CT · On-site

$119K - $132K/yr

Write Python scripts used for systems administration, automation, andback-end operational processes ... Enjoy access to health, dental, disability, and life insurance, paid holidays and vacation, 401(k) ...

ISO New England Inc.

Data Scientist

Windsor, CT · On-site

$86 - $146/hr

Leverage a curious mindset, initiative, and "elbow grease" to enhance existing processes, and to ... This role is also eligible for an annual performance bonus, comprehensive health insurance (medical ...

USM

Data Architect

Windsor, CT · On-site

$55 - $60/hr

Contribute to data tool standards and governance processes. Assist with evaluating data complexity ... Prior experience with financial services, retirement, insurance, or medical records industry highly ...

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All JobsInsurance Data Processing JobsInsurance Data Processing Jobs in Connecticut

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 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

Berkley

Greenwich, CT

$128K - $154K/yr

Full-time

Re-posted 14 days 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 problemsolving skills to design, build, and operate data platforms that support actuaries, analytics, modeling, and AIenabled workflows.

This role is suited to someone who is technically strong, comfortable working independently, and able to translate complexity into robust, welldesigned systems that others can rely on.

The position emphasizes engineering rigor, highquality code, system reliability, and sound judgment over oneoff 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 productionquality 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., Sparkbased pipelines).
  • Partner with actuaries, analytics, data science, and business teams to enable modeling and AI uses.
  • Apply AIassisted engineering approaches, including LLMenabled 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, tradeoffs, and limitations clearly to technical and nontechnical 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 LLMbased 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 DetailsSponsorship not Offered for this RoleEmployment Type: OTHER

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