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Insurance Data Engineer Jobs in Philadelphia, PA

Chubb

AVP, Lead Data Engineer

Philadelphia, PA · On-site

$109K - $131K/yr

Chubb is a world leader in insurance. With operations in 54 countries, Chubb provides commercial ... data engineering experience, including hands-on ETL/ELT development, data warehouse design, and ...

Amerihealth Caritas

Azure Data Engineer

Newtown Square, PA · Hybrid

$109K - $131K/yr

Role Overview The Azure Data Engineer designs, builds, and optimizes large scale cloud data ... events, Health insurance coverage for you and your dependents on Day 1, 401(k) Tuition ...

Amerihealth Caritas

Azure Data Engineer

Newtown Square, PA · Hybrid

$109K - $131K/yr

Role Overview The Azure Data Engineer designs, builds, and optimizes large scale cloud data ... events, Health insurance coverage for you and your dependents on Day 1, 401(k) Tuition ...

Apex Systems

Sr Data Engineer

Philadelphia, PA · On-site

$55 - $80/hr

Job#: 3034798 Sr Data Engineer Location: Philadelphia, Pennsylvania (Remote) Employment Type ... other insurance plans that offer an optional layer of financial protection. We offer an ESPP ...

New

Bridge Flair LLC

Data Engineer Only W2

Malvern, PA · On-site

$112K - $134K/yr

We are seeking an experienced Data Engineer with strong expertise in Python, AWS Glue, ETL development, and Annuity/Insurance domain knowledge. The ideal candidate will be responsible for designing ...

New

Aegon

Lead Data Engineer

Philadelphia, PA

$115K - $138K/yr

Our insurance, retirement, and investment solutions help people make the most of what's important ... Summary The Lead Data Engineer is responsible for the design, architecture and support of systems ...

Tata Consultancy Service Limited

Data Engineer

Malvern, PA · On-site

$120K - $130K/yr

... data integration pipelines using AWS Glue, PySpark, and Python. • Develop and optimize data ... Insurance Options: Auto & Home Insurance, Identity Theft Protection. Convenience & Professional ...

New

NFI Industries

Senior Data Engineer

Camden, NJ · On-site

$104K - $139K/yr

Join our innovative Data & Analytics team as a Senior Data Engineer , where you'll play a pivotal ... Insurance, Paid Time Off, and Paid Parental Leave, among other benefit plan options. Equal ...

Chubb

AVP, Lead Data Engineer

Philadelphia, PA · On-site

$152K - $221K/yr

By joining Chubb as Lead Data Engineer for our North America Finance & Actuarial data platform, you ... Insurance industry experience preferred; P&C domain knowledge (financial reporting, actuarial data ...

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Showing results 1-20

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 Jul 16, 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.

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 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 July 2026, with employment types broken down into 77% Full Time, and 23% Contract. Highlights an 79% In-person, 15% Hybrid, and 6% Remote job distribution, with an average salary of $130,895 per year, or $62.9 per hour.
Senior Data and AI Engineer (Insurance Domain)

Senior Data and AI Engineer (Insurance Domain)

Accord Technologies Inc.

Philadelphia, PA • On-site

$115K - $138K/yr

Contractor

Re-posted 2 days ago

Job description

Senior Data and AI Engineer (Insurance Domain)
Location:  Philadelphia, PA
Position type: Onsite role (need NJ, PA based candidates who can join immediately)
Tax type: W2 contract
Candidate should be available to start by next week.

Job Description:
The role owns the full technical stack from the architecture slide: connectors and 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.

Knowledge Graph & Semantic Technologies (Must-Have)

•            3+ years hands-on experience with graph databases (GraphDB, Neo4j, Stardog)in a production or advanced PoC context

•            Working proficiency with semantic web standards

•            Experience loading, validating, and querying ontologies in a triple store environment

•            Familiarity with ontology authoring tools (Protégé, Metaphactory) sufficient to collaborate with the Data Consultant on model iterations

AI / ML Engineering & LLM Integration (Must-Have)

•            Demonstrated experience building RAG (Retrieval-Augmented Generation) pipelines, ideally with agentic orchestration patterns

•            Hands-on experience with vector databases (Azure AI Search, pgvector, Pinecone, Weaviate, or Qdrant) for embedding and retrieval

•            Experience integrating LLM APIs (Anthropic Claude, OpenAI GPT, or Azure OpenAI) with prompt engineering, guardrails, and citation enforcement

•            Familiarity with NL-to-SPARQL or NL-to-SQL generation techniques, including few-shot prompting and schema-grounding approaches

•            Understanding of AI safety guardrails: prompt injection defense, output sandboxing, and confidence scoring

Delivery & Collaboration (Must-Have)

•            Comfortable operating in an accelerated 8-week delivery timeline with weekly milestone gates and hard dependencies

•            Ability to work closely with a Data Modeller/Ontologist to translate conceptual models into working technical implementations

•            Experience in financial services or insurance data environments is preferred but not required, provided strong technical depth in the above areas

Data Engineering & Microsoft Fabric (Good to-Have)

•            Strong Python engineering skills with experience building data pipelines, ETL/ELT processes, and metadata ingestion frameworks

•            Experience with Microsoft Fabric ecosystem: OneLake, Lakehouse, Notebooks, Data Factory / pipelines, and Medallion architecture (Bronze/Silver/Gold)

•            Familiarity with JDBC/ODBC connectors, REST API integration, and file parsing (Excel, CSV, JSON) for metadata extraction

•            Experience with Trino, Databricks SQL, or equivalent federated query engines