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Insurance Data Engineer Jobs in Riverside, CT (NOW HIRING)

Brookfield

Senior Data Engineer

New York, NY

$113K - $160K/yr

Argo and Farm Family partner with agents and brokers to provide insurance solutions that enable businesses to manage risks with confidence. Senior Data Engineer AI-First Data Strategy for P&C ...

Berkley

Data Engineer

Greenwich, CT

$128K - $154K/yr

Insurance and Reinsurance and Monoline Excess. Led by our Executive Chairman, founder and largest ... We are seeking a Data Engineer with strong engineering, coding, and problemsolving skills to design ...

Berkley

Data Engineer

Greenwich, CT · On-site

$128K - $154K/yr

Insurance and Reinsurance and Monoline Excess. Led by our Executive Chairman, founder and largest ... Responsibilities We are seeking a Data Engineer with strong engineering, coding, and problem ...

Berkley

Data Engineer

Greenwich, CT

$128K - $154K/yr

Insurance and Reinsurance and Monoline Excess. Led by our Executive Chairman, founder and largest ... Responsibilities We are seeking a Data Engineer with strong engineering, coding, and problemsolving ...

EPIC Brokers

Lead Insurance Data Scientist

Manhattan, NY · On-site

$150/hr

Working within a lean, high-impact team, you will collaborate closely with solution engineers and ... data from a variety of insurance-related sources. • Perform exploratory data analysis to identify ...

Archgroup

Manager, Data Engineer (Remote)

New York, NY · Remote

$100K - $174K/yr

You will also guide engineers and reinforce strong delivery practices, while advancing the team ... Insurance data modelingforanalytics and actuarial-ready data structures * MLOpsfamiliarity ...

Archgroup

Manager, Data Engineer (Remote)

New York, NY · Remote

$100K - $174K/yr

You will also guide engineers and reinforce strong delivery practices, while advancing the team ... Insurance data modelingforanalytics and actuarial-ready data structures * MLOpsfamiliarity ...

Arlo

Data Engineer

New York, NY · On-site

$180K - $220K/yr

Arlo is rebuilding health insurance for small businesses from first principles: making sure as much ... We're hiring a Data Engineer to build and maintain the pipelines, models, and monitoring systems ...

Arlo

Data Engineer

New York, NY · On-site

$180K - $220K/yr

Arlo is rebuilding health insurance for small businesses from first principles: making sure as much ... We're hiring a Data Engineer to build and maintain the pipelines, models, and monitoring systems ...

Cerity Partners

Data Engineer

New York, NY · On-site

$140K - $180K/yr

As a data engineer at Cerity Partners you will play a leading role maintaining the current--and ... Health, dental, and vision insurance - day 1! * 401(k) savings and investment plan options with 4% ...

BBR Partners

Data Engineer

New York, NY · On-site +1

$110K - $125K/yr

POSITION OVERVIEW BBR Partners is seeking a Data Engineer to contribute to the build-out and ... Company subsidized health, dental and vision insurance for employee, partner, and dependents ...

Tabs

Data Engineer

New York, NY · On-site

$160K - $195K/yr

About the role You'll be the first Data Engineer at Tabs, building the core data infrastructure ... Voluntary insurances (Life, Hospital, Critical Illness, Accident) * Employee Assistance Program ...

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All JobsInsurance Data Engineer JobsInsurance Data Engineer Jobs in Riverside, CT

Insurance Data Engineer information

See Riverside, CT salary details

$47.2K

$137.5K

$188.1K

How much do insurance data engineer jobs pay per year?

As of Jun 25, 2026, the average yearly pay for insurance data engineer in Riverside, CT is $137,460.00, according to ZipRecruiter salary data. Most workers in this role earn between $121,300.00 and $145,700.00 per year, depending on experience, location, and employer.

What health insurance covers Wegovy?

As an Insurance Data Engineer, understanding insurance coverage is essential. Coverage for Wegovy, a prescription weight management medication, varies by insurance plan and provider. Many health insurance plans, including some employer-sponsored plans and Medicare, may cover Wegovy if prescribed for approved indications, but prior authorization is often required.

What is the best cheapest insurance?

As an Insurance Data Engineer, evaluating the cheapest insurance involves analyzing data from multiple providers to identify affordable options that meet coverage needs. Comparing quotes, understanding policy details, and using data analysis tools can help find cost-effective insurance plans. However, the cheapest option may not always offer the best coverage, so balancing cost and coverage is essential.

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.

Does health insurance cover a pacemaker?

As an Insurance Data Engineer, you should know that health insurance typically covers pacemaker implantation and related procedures if deemed medically necessary, though coverage details vary by plan. Patients usually need prior authorization, and coverage may include device costs, surgery, and follow-up care. It is important to review specific policy terms and provider networks for accurate coverage information.

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.

Who does the cheapest insurance?

Insurance Data Engineers analyze data to help insurance companies identify cost-effective policies and pricing strategies. The cheapest insurance options typically depend on factors like coverage needs, customer profile, and provider discounts, rather than a specific role. Consumers should compare quotes from multiple providers to find the most affordable coverage.

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.
What cities near Riverside, CT are hiring for Insurance Data Engineer jobs? Cities near Riverside, CT with the most Insurance Data Engineer job openings:
Insurance Data Engineer jobs near you

Data Engineer- Enterprise Data Hub (Insurance Domain, AWS)

Accord Technologies Inc.

New York, NY • On-site

Contractor

Posted 20 days ago

Job description

Data Engineer – Enterprise Data Hub (Insurance Domain, AWS)
Location: New York, NY
Duration: long term
Position type: W2 contract 
Position type:

We are looking for Data Engineer supporting the development and maintenance of Enterprise Data Hub within the insurance domain. The ideal candidate will have strong experience in AWS cloud services, data pipeline development, and insurance data models. This role will play a key part in enabling data-driven decision-making across the organization. The successful candidate will collaborate closely with data architects, enterprise architects, infrastructure, and other cross-functional teams to build data pipelines that are scalable and aligned to best practices for data management, change management, integration, and analysis This is an exciting opportunity to work on cutting-edge technologies, solve complex challenges, and drive impactful insights that fuel our company's success. The role reports to the Enterprise Data Hub Product Lead.

This role is ideal for a proactive and detail-oriented professional who is passionate about development, governance and controls. If you thrive in a dynamic environment and are committed to maintaining high standards of IT control, this position offers a rewarding opportunity to make a significant impact.

Your skills and abilities should include:

  • 10+ years of experience in data engineering or related roles, in the insurance industry.(Re-insurance)
  • Strong hands-on experience with AWS data services (e.g., Glue, Redshift, S3, Athena, Lambda, EMR).
  • Proficiency in SQL, Python, and data modelling.
  • Experience with ETL tools and frameworks.
  • Familiarity with insurance data domains (e.g., claims, policy, billing).
  • Understanding of data governance, lineage, and compliance (e.g., HIPAA, GDPR).
  • Experience with CI/CD and version control tools (e.g., Git, CodePipeline).
  • AWS or Solutions Architect certifications are not required but preferred.
  • Experience with data lakes and lakehouse architectures is a strong plus.
  • Exposure to BI tools (e.g., Power BI, Tableau, QuickSight) is preferred.
  • Bachelor’s or Master’s degree in Computer Science, Data Engineering, or related field is a strong plus.
  • Excellent organizational, communication, and interpersonal skills. 
  • Ability to work individually with limited oversight.
  • Ability to prioritize, multi-task, and maintain flexibility in a fast-paced, changing environment.
  • Demonstrated ability to influence and work effectively within a global organization with employees at all levels.
  • Motivated, team-oriented, with strong problem-solving and project management skills.

Key Responsibilities

  • Design, build, and maintain scalable data pipelines and ETL processes for the Enterprise Data Hub.
  • Implement data ingestion, transformation, and storage solutions using AWS services (e.g., Glue, Redshift, S3, Athena, Lambda, EMR).
  • Work with structured and unstructured data from variousinsurance systems (e.g., policy, claims, underwriting).
  • Collaborate with data architects, analysts, and business stakeholders to understand data requirements.
  • Collaborate with enterprise architects to understand integration design patterns. 
  • Collaborate with infrastructure to align to best practices for code deployments and change management.
  • Ensure data quality, integrity, and governance across the data lifecycle.
  • Optimize data workflows for performance, scalability, and cost-efficiency.
  • Support data cataloguing and metadata management initiatives.
  • Implement security and compliance best practices for sensitive insurance data