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Insurance Data Engineer Jobs in Philadelphia, PA

Accord Technologies Inc.

Senior AI Engineer

Philadelphia, PA · On-site

$123K - $163K/yr

Senior AI Engineer (Insurance domain and Data Background) Philadelphia, PA (Hybrid Day 1 onsite) Position type: W2 contract Role: The Senior Data & AI Engineer owns the full technical stack ...

BakerHostetler

Data Solutions Engineer

Philadelphia, PA

$109K - $131K/yr

Join our team as a Data Solutions Engineer, where you will play a key role in designing and ... Life Insurance * Voluntary Accident Insurance - Self and Family * Short and Long-Term Disability

Stable Industry Niche Software Company Serving a Very Recession Resistant Industry

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Modern Stack Developer Claude Code, GraphQL and Health Insurance Apps

Bala Cynwyd, PA · Remote

$110K - $140K/yr

Proven experience as a Full-Stack Engineer with deep expertise in TypeScript, GraphQL, Node.js, ... Familiarity with LangGraph, LangSmith, AI agents, or building complex data-migration and ...

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Lincoln Financial

Sr Assoc Data Engineer

Radnor, PA · On-site

$84K - $135K/yr

We focus on identifying a clear path to financial security, with products including annuities, life insurance, group protection, and retirement plan services. With our 120-year track record of ...

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All JobsInsurance Data Engineer JobsInsurance Data Engineer Jobs in Philadelphia, PA

Insurance Data Engineer information

See Philadelphia, PA salary details

$44.9K

$130.9K

$179.1K

How much do insurance data engineer jobs pay per year?

As of Sep 6, 2026, the average yearly pay for insurance data engineer in Philadelphia, PA is $130,895.00, according to ZipRecruiter salary data. Most workers in this role earn between $115,500.00 and $138,700.00 per year, depending on experience, location, and employer.

What is an insurance data engineer?

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.

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 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 Philadelphia, PA?

For Insurance Data Engineer jobs in Philadelphia, PA, the most frequently searched job titles are:

What job categories do people searching Insurance Data Engineer jobs in Philadelphia, PA look for?

The top searched job categories for Insurance Data Engineer jobs in Philadelphia, PA are:

What cities near Philadelphia, PA are hiring for Insurance Data Engineer jobs?

Cities near Philadelphia, PA with the most Insurance Data Engineer job openings:

Insurance Data Engineer jobs near you
Infographic showing various Insurance Data Engineer job openings in Philadelphia, PA as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 21% Part Time, and 5% Contract. Highlights an 92% Physical, 1% Hybrid, and 7% Remote job distribution, with an average salary of $130,895 per year, or $62.9 per hour.

Senior AI Engineer

Accord Technologies Inc.

Philadelphia, PA • On-site

$123K - $163K/yr

Contractor

Re-posted yesterday

Job description

Job Description: Senior AI Engineer (Insurance domain and Data Background)
Philadelphia, PA (Hybrid Day 1 onsite)
Position type: W2 contract
 

Role: 
The Senior Data & AI Engineer owns the full technical stack, including connectors, ingestion framework, OneLake Medallion staging, GraphDB triple store, Vector Index, Agentic RAG orchestrator, LLM gateway, guardrails, and the consumption UI with conversational chat, SPARQL trace explainability, and graph explorer.

Responsibilities:

  • Develop and maintain graph databases (GraphDB, Neo4j, Stardog) in production or advanced PoC setups.
  • Load, validate, and query ontologies within triple store environments.
  • Collaborate with Data Consultants on ontology modeling using tools like Protégé or Metaphactory.
  • Build and optimize RAG pipelines with agentic orchestration.
  • Work with vector databases for embedding and retrieval tasks.
  • Integrate LLM APIs (e.g., Anthropic Claude, OpenAI GPT, Azure OpenAI) with prompt engineering, guardrails, and citation mechanisms.
  • Develop NL-to-SPARQL or NL-to-SQL generation solutions, employing few-shot prompting and schema grounding.
  • Implement AI safety measures including prompt injection defenses, output sandboxing, and confidence scoring.
  • Operate within an 8-week delivery cycle with weekly milestones.
  • Collaborate closely with data modeling and ontologist teams.
  • Leverage experience in financial services or insurance data environments where possible.

 Required Skills:

  • 3+ years of hands-on experience with graph databases and semantic web standards.
  • Proficiency in ontology authoring tools.
  • Proven experience with RAG pipelines and agentic orchestration. 
  • Expertise in vector databases and LLM API integration.
  • Knowledge of NL-to-SPARQL/NL-to-SQL conversion techniques.
  • Strong understanding of AI safety protocols.
  • Project management skills suitable for rapid development cycles.
  • Excellent collaboration and communication skills.