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Insurance Data Engineer Jobs in Springfield, MA (NOW HIRING)

Munich RE

Data Modeler

Hartford, CT

$55.25 - $71.50/hr

Own the design of canonical data models for delegated insurance covering Contract, Premium/Risk ... Collaborate with engineering teams to implement models on Distributed big-data processing platforms ...

Munich Re

Data Modeler

Hartford, CT · On-site

$55.25 - $71.50/hr

Own the design of canonical data models for delegated insurance covering Contract, Premium/Risk ... Collaborate with engineering teams to implement models on Distributed big-data processing platforms ...

Chubb

Enterprise Information Architect

Simsbury, CT

... data engineers and architects on data governance best practices, ensuring data integrity, quality, security, and compliance with industry regulations. Chubb is a world leader in insurance. With ...

Infosys

GCP Data Engineer with Python

Hartford, CT · On-site

$115.50K - $138.70K/yr

Insurance (Accident, Critical Illness , Hospital Indemnity, Legal) * 401(k) plan and contributions ... Required Skill and Experience • Hands-on experience in Python programming • Familiarity with ET ...

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Insurance Data Engineer information

See Springfield, MA salary details

$44.3K

$129.3K

$176.9K

How much do insurance data engineer jobs pay per year?

As of May 30, 2026, the average yearly pay for insurance data engineer in Springfield, MA is $129,263.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,100.00 and $137,000.00 per year, depending on experience, location, and employer.

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.

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 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 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.

What are popular job titles related to Insurance Data Engineer jobs in Springfield, MA? For Insurance Data Engineer jobs in Springfield, MA, the most frequently searched job titles are:
What job categories do people searching Insurance Data Engineer jobs in Springfield, MA look for? The top searched job categories for Insurance Data Engineer jobs in Springfield, MA are:
What cities near Springfield, MA are hiring for Insurance Data Engineer jobs? Cities near Springfield, MA with the most Insurance Data Engineer job openings:
Insurance Data Engineer jobs near you
Senior Staff AI Data Engineer - Hybrid

Senior Staff AI Data Engineer - Hybrid

The Hartford Financial Services Group, Inc.

Hartford, CT • On-site

$106.90K - $145.30K/yr

Full-time

Posted 15 days ago

The Hartford rating

8.8

Company rating: 8.8 out of 10

Based on 103 frontline employees who took The Breakroom Quiz

53rd of 259 rated insurance

Job description

Sr Staff Data Engineer - GE07DE
We're determined to make a difference and are proud to be an insurance company that goes well beyond coverages and policies. Working here means having every opportunity to achieve your goals - and to help others accomplish theirs, too. Join our team as we help shape the future.
Join our team as a Senior Staff AI Data Engineer and lead the charge in developing cutting-edge AI solutions and data engineering strategies. Embrace our core values of innovation, collaboration, and excellence as you unlock unparalleled growth opportunities in the dynamic field of AI and data engineering. Shape the future of technology with us! Apply now to be part of our innovative journey and make a significant impact!
This role will have a Hybrid work schedule, with the expectation of working in an office location (Hartford, CT; Danbury, CT; Chicago, IL; Columbus, OH; and Charlotte, NC) 3 days a week (Tuesday through Thursday).
Primary Job Responsibilities
  • AI Data Engineering lead responsible for Implementing AI data pipelines that bring together structured, semi-structured and unstructured data to support AI and Agentic solutions. This Includes pre-processing with extraction, chunking, embedding and grounding strategies to get the data ready.
  • Develop AI-driven systems to improve data capabilities, ensuring compliance with industry best practices.
  • Implement efficient Retrieval-Augmented Generation (RAG) architectures and integrate with enterprise data infrastructure.
  • Collaborate with cross-functional teams to integrate solutions into operational processes and systems supporting various functions.
  • Stay up to date with industry advancements in GenAI and apply modern technologies and methodologies to our systems.
  • Design, build and maintain scalable and robust real-time data streaming pipelines using technologies such as SnowPipe.
  • Develop data domains and data products for various consumption archetypes including Reporting, Data Science, AI/ML, Analytics etc
  • Ensure the reliability, availability, and scalability of data pipelines and systems through effective monitoring, alerting, and incident management.
  • Implement best practices in reliability engineering, including redundancy, fault tolerance, and disaster recovery strategies.
  • Collaborate closely with DevOps and infrastructure teams to ensure seamless deployment, operation, and maintenance of data systems.
  • Mentor junior team members and engage in communities of practice to deliver high-quality data and AI solutions while promoting best practices, standards, and adoption of reusable patterns.
  • Develop graph database solution for complex data relationships supporting AI systems.
  • Apply GenAI solutions to insurance-specific data use cases and challenges.
  • Partner with architects and stakeholders to influence and implement the vision of the AI and data pipelines while safeguarding the integrity and scalability of the environment.

Skills
  • Strong Technical Knowledge (AI solution leveraging Cloud and modern solutions)
  • Able to communicate effectively with both technical and non-technical teams and influence
  • Collaboration across teams, decision making, conflict resolution and relationship building skills.
  • Experience in mentoring and developing Junior AI or Data Engineers.
  • Knowledge of evolving industry design patterns for AI.
  • Strong planning, organization, and execution skills.
  • Ability to provide Thought Leadership to dynamic and collaborative teams, demonstrating excellent interpersonal skills and time management capabilities.
  • Ability to understand and align deliverables to the departmental and organization strategies and objectives.
  • Ability to lead successfully in a lean, agile, and fast-paced organization, leveraging Scaled Agile principles and ways of working.
  • Leader and team player with a transformation mindset.
  • Ability to translate complex technical topics into business solutions and strategies, as well as turn business requirements into a technical solution.

Qualifications
  • Candidates must be authorized to work in the US without company sponsorship. The company will not support the STEM OPT I-983 Training Plan endorsement for this position.
  • Bachelor's in Computer Science, Artificial Intelligence, or a related field.
  • 8+ years of data engineering experience including Data solutions, SQL and NoSQL, Snowflake, ETL/ELT tools, CICD, Python/Spark, Datamesh or Data Fabric.
  • 1+ years of data engineering experience focused on supporting Generative AI technologies
  • Strong hands-on experience implementing production ready enterprise grade GenAI data solutions.
  • Experience with prompt engineering techniques for large language models.
  • Experience in implementing Retrieval-Augmented Generation (RAG) pipelines, integrating retrieval mechanisms with language models.
  • Experience of vector databases and graph databases, including implementation and optimization.
  • Experience in processing and leveraging unstructured data for GenAI applications.
  • Proficiency in implementing scalable AI driven data systems supporting agentic solution (AWS Lambda, S3, EC2, Lang chain, Langgraph).
  • Strong programming skills in Python and familiarity with deep learning frameworks such as PyTorch or TensorFlow.
  • Experience with building AI pipelines that bring together structured, semi-structured and unstructured data. This includes pre-processing with extraction, chunking, embedding and grounding strategies, semantic modeling, and getting the data ready for Models and Agentic solutions.
  • Experience in vector databases, graph databases, NoSQL, Document DBs, including design, implementation, and optimization. (e.g., AWS open search, GCP Vertex AI, Neo4j, Spanner Graph, Neptune, Mongo, DynamoDB etc.).
  • Experience in implementing data governance practices, including Data Quality, Lineage, Data Catalogue capture, holistically, strategically, and dynamically on a large-scale data platform.
  • Experience with cloud platforms (AWS or GCP or Azure)
  • Strong written and verbal communication skills and ability to explain technical concepts to various stakeholders.

Preferred Qualifications:
  • Experience in multi cloud hybrid AI solutions.
  • AI Certifications
  • Experience in P&C industry
  • Knowledge of natural language processing (NLP) and computer vision technologies.
  • Contributions to open-source AI projects or research publications in the field of Generative AI.

Compensation
The listed annualized base pay range is primarily based on analysis of similar positions in the external market. Actual base pay could vary and may be above or below the listed range based on factors including but not limited to performance, proficiency and demonstration of competencies required for the role. The base pay is just one component of The Hartford's total compensation package for employees. Other rewards may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition. The annualized base pay range for this role is:
$135,040 - $202,560
Equal Opportunity Employer/Sex/Race/Color/Veterans/Disability/Sexual Orientation/Gender Identity or Expression/Religion/Age
About Us | Our Culture | What It's Like to Work Here | Perks & Benefits

What The Hartford employees say

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About Hartford

Sourced by ZipRecruiter

Hartford Financial Services Group, widely recognized as The Hartford, is a renowned company based in Hartford, CT, US. Established in 1810, it has evolved into an industry leader in the insurance and financial services sector, proudly serving more than one million businesses in the US. The Hartford is committed to offering a gamut of insurance products that include homeowners, automobile, and business insurance as well as employee benefits and mutual funds. The company’s core values revolve around customer-focused innovations, diversity and inclusion, and ethical dealings that have earned them a customer-centric reputation. This shapes their mission which revolves around aiding their clients to overcome unforeseen obstacles and enhancing their wealth over time. Among the company's noted accomplishments is being consistently listed among the World's Most Ethical Companies, a testament to their unwavering commitment towards responsible business practices.

Industry

Finance and insurance

Company size

10,000+ Employees

Headquarters location

Hartford, CT, US

Year founded

1810

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