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Insurance Data Engineer Jobs in New York (NOW HIRING)

EXL

Fabric Analytics Data Engineer

Newark, NJ · On-site

EXL is seeking a Fabric Analytics Data Engineer to architect and implement data solutions using ... support insurance datasets such as policy, claims, billing, actuarial, and customer information ...

ECLARO

Data Engineer

Rutherford, NJ · On-site

$116K - $140K/yr

ECLARO is hiring for a Data Engineer for their client, a leading insurance company providing risk management services to the energy industry. The role involves developing and testing data integration ...

Brookfield

Senior Data Engineer

New York, NY · On-site

$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 ...

Inizio Partners

Lead AWS Data Engineer

Jersey City, NJ · On-site

$107K - $140K/yr

... Data Engineer to support complex data engineering initiatives within our insurance data and ... Architect scalable ELT/ETL workflows and data warehouse models supporting insurance analytics use ...

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 ... We are seeking a Data Engineer with strong engineering, coding, and problemsolving skills to design ...

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 ...

Tandym Tech

Data Engineer

Millburn, NJ · On-site

$114K - $137K/yr

Strong data engineering fundamentals with ETL experience * Advanced data modeling experience with ... Background in Property and Casualty Insurance * Bachelor's degree in computer science or a related ...

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)

Jersey City, NJ · 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)

Jersey City, NJ · 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 ...

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Insurance Data Engineer information

How much do insurance engineers make?

Insurance data engineers typically earn a median salary ranging from $80,000 to $120,000 annually, depending on experience, location, and industry. Senior roles or those with specialized skills in data pipelines, cloud platforms, and programming languages like Python or SQL can command higher salaries. Compensation may also include benefits such as bonuses and professional development opportunities.

What engineers make $500,000?

Senior data engineers, including those working in specialized fields like insurance data engineering, can earn $500,000 or more annually, especially with extensive experience, advanced skills in cloud platforms, and leadership roles. High compensation is often associated with seniority, complex data systems, and working in competitive markets or large organizations.

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.

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.

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.

Is AI replacing data engineers?

AI is transforming the role of data engineers by automating routine tasks such as data cleaning and integration, but it does not replace the need for skilled professionals to design, manage, and oversee data infrastructure. Data engineers are essential for building scalable data pipelines, ensuring data quality, and implementing AI solutions effectively. Their expertise remains critical in managing complex data environments and integrating AI tools into business processes.

What engineers make 300,000 a year?

Senior data engineers, including those working in specialized fields like insurance data engineering, can earn $300,000 or more annually, especially with extensive experience, advanced skills in SQL, Python, cloud platforms, and certifications. High-level roles often involve leadership, complex data architecture, and strategic decision-making, typically in large organizations or with specialized expertise.
What are popular job titles related to Insurance Data Engineer jobs in New York? For Insurance Data Engineer jobs in New York, the most frequently searched job titles are:
What job categories do people searching Insurance Data Engineer jobs in New York look for? The top searched job categories for Insurance Data Engineer jobs in New York are:
What cities in New York are hiring for Insurance Data Engineer jobs? Cities in New York with the most Insurance Data Engineer job openings:
Insurance Data Engineer jobs near you
Infographic showing various Insurance Data Engineer job openings in New York as of July 2026, with employment types broken down into 77% Full Time, and 23% Contract. Highlights an 81% In-person, and 19% Hybrid job distribution.
Data Engineer- Enterprise Data Hub (Insurance Domain, AWS)

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

Accord Technologies Inc.

New York, NY • On-site

Contractor

Posted 21 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