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Insurance Data Engineer Jobs in Tallahassee, FL (NOW HIRING)

Lead, Data Engineer

Tallahassee, FL ยท Remote

$127K - $236K/yr

Lead, Data Engineer Job Code: 41065 Job Location: Melbourne, FL or Remote Opportunity Job Schedule ... L3Harris also offers a variety of benefits, including health and disability insurance, 401(k) match ...

Principal, Data Engineer

Tallahassee, FL ยท On-site +1

$153K - $284K/yr

Job Title: Principal, Data Engineer Job Code: 41066 Job Location: Melbourne, FL; or Remote ... L3Harris also offers a variety of benefits, including health and disability insurance, 401(k) match ...

Data Integration Developer Department: Information Technology Location: Thomasville, GA Reports to ... Pet insurance * Employee discount program * Tuition assistance * Paid time off and 11 paid holidays ...

DATA ANALYST - 48001093

Tallahassee, FL ยท On-site

$60K - $65K/yr

Proficiency in one or more programming languages (e.g., SQL, SAS, Python, R) * Proficiency in one ... Health insurance (over 80% employer paid) * Basic life insurance policy (100% employer paid)

DATA ANALYST - 48001093

Tallahassee, FL ยท On-site

$60K - $65K/yr

Proficiency in one or more programming languages (e.g., SQL, SAS, Python, R) * Proficiency in one ... Health insurance (over 80% employer paid) * Basic life insurance policy (100% employer paid)

Lead Data Scientist

Thomasville, GA ยท On-site

$144K - $198K/yr

Engineer trustworthy data: turn large, messy operational data into well-structured, trusted ... Pursuit Aerospace also offers a variety of benefits, including health and disability insurance ...

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Insurance Data Engineer information

See Tallahassee, FL salary details

$42.3K

$123.2K

$168.6K

How much do insurance data engineer jobs pay per year?

As of Aug 26, 2026, the average yearly pay for insurance data engineer in Tallahassee, FL is $123,219.00, according to ZipRecruiter salary data. Most workers in this role earn between $108,800.00 and $130,600.00 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 Tallahassee, FL?

For Insurance Data Engineer jobs in Tallahassee, FL, the most frequently searched job titles are:

What job categories do people searching Insurance Data Engineer jobs in Tallahassee, FL look for?

The top searched job categories for Insurance Data Engineer jobs in Tallahassee, FL are:

What cities near Tallahassee, FL are hiring for Insurance Data Engineer jobs?

Cities near Tallahassee, FL with the most Insurance Data Engineer job openings:

Lead, Data Engineer

L3HHCM20

Tallahassee, FL โ€ข Remote

$127K - $236K/yr

Full-time

Medical, Retirement, PTO

Re-posted 10 days ago


Job description

Job Title:ย Lead, Data Engineerย 

Job Code:ย 41065

Job Location:ย Melbourne, FL or Remote Opportunity

Job Schedule:ย 9/80: Employees work 9 out of every 14 days - totaling 80 hours worked - and have every other Friday off

Job Description:

L3Harris Enterprise Data and AI team is seeking a Data Engineer with experience in managing enterprise-level data life cycle processes. This role includes overseeing data ETL/ELT pipelines, ensuring adherence to data standards, maintaining data frameworks, conducting data cleansing, orchestrating data pipelines, and ensuring data consolidation. The selected individual will play a pivotal role in maintaining ontologies, building scalable data solutions, and developing dashboards to provide actionable insights for the enterprise within Palantir Foundry. This position will support the company's modern data platform, Unified Data Layer, focusing on data pipeline development and maintenance, data platform design, documentation, and user training. The goal is to ensure seamless access to data for all levels of the organization, empowering decision-makers with clean, reliable data.

Essential Functions:

  • Provide architectural oversight for the company's data platform and related initiatives, ensuring alignment with company standards and best practices
  • Assist development initiatives with design reviews, offering guidance on architecture and data modeling
  • Lead design reviews for proposed solutions, including data sourcing, data pipelines, data models, and ontology resources, providing actionable feedback to enhance design scalability
  • Assist and develop architectural artifacts, perform requirements decomposition, and develop other documentation to support the software development lifecycle (SDLC)
  • Support the SDLC process by participating in data architecture review sessions, reviewing proposed solutions for compliance with architectural standards
  • Oversee and provide guidance for data pipelines, ensuring scalability, reusability, and performance
  • Utilize Palantir Foundry to perform data integration and ontology management to support big data analytics at scale
  • Collaborate with cross-functional teams to define data governance, metadata, and ontology standards, ensuring consistency and clarity across the data platform and enterprise
  • Remain current with emerging data technologies and frameworks to recommend improvements to the data platform architecture

Qualifications:

  • Bachelor's Degree and minimum 9ย years prior Palantir experience orย Graduate Degree and a minimum of 7ย years of prior Palantir experienceย In lieu of degree, minimum 13ย years of prior Palantir experience.
  • Minimum of 4ย years of experience with Data Pipeline development or ETL tools such as Palantir Foundry, Azure Data Factory, SSIS, or Python.
  • Minimum of 4ย years of experience in Data Integration.

Preferred Additional Skills:

  • Experience supporting or implementing solutions that leverage Generative AI capabilities, including Retrieval-Augmented Generation (RAG), semantic search, and LLM integration
  • Experience with Palantir Foundry tools such as Ontology Manager, Compass, Code Repository, Solution Designer, OSDK, AI FDE, and AIP Analyst
  • Understanding of BI (Business Intelligence) & DW (Data Warehouse) development methodologies
  • Experience with Python, Pandas, Databricks, JavaScript, Typescript or other scripting languages
  • Experience with AI tools such as OpenAI, Palantir AIP, Snowflake Cortex, or similar
  • Hands on Experience with design, development of Data Pipelines in Palantir Foundry Pipeline Builder or Code Repository, or similar technologies leveraging PySpark and Spark SQL
  • Familiarity with SDLC processes and architecture review or data governance board processes

In compliance with pay transparency requirements, the salary range for this role in California, Massachusetts, New Jersey, Washington, and the Greater D.C, Denver, or NYC areas is $127,000-$236,500. The salary range for this role in Colorado state, Hawaii, Illinois, Maryland, Minnesota, New York state, and Vermont is $110,500-$205,500. This is not a guarantee of compensation or salary, as final offer amount may vary based on factors including but not limited to experience and geographic location. L3Harris also offers a variety of benefits, including health and disability insurance, 401(k) match, flexible spending accounts, EAP, education assistance, parental leave, paid time off, and company-paid holidays. The specific programs and options available to an employee may vary depending on date of hire, schedule type, and the applicability of collective bargaining agreements.

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