Data Engineer - ETL

Company Details

Carolina Casualty is a member company of W. R. Berkley Corporation, an insurance holding company that is among the largest commercial lines insurance writers in the United States. We specialize in liability, physical damage, cargo and other insurance solutions for the commercial auto markets including trucking, public transportation and others.

Join Carolina Casualty, where innovation meets purpose.

Carolina Casualty is a proud member of W. R. Berkley Corporation, one of the largest commercial lines insurers in the country. What sets us apart is not just our size, but how we work and who we are.

We specialize in liability, physical damage, cargo, and other insurance solutions for the commercial auto market, including trucking and public transportation industries that keep America moving. Our team tackles real, complex challenges for the people and businesses that make that possible every day.

At CCIC, we live by three simple truths:

Always do right. Integrity is not just a slogan. It guides every decision we make.

Everything counts; everyone matters. Every role, every voice, and every contribution help shape who we are as an organization.

Embrace innovation and act responsibly. We are willing to challenge the status quo while remaining thoughtful and committed to our people, customers, and partners.

If you are looking for a place where your work makes an impact, your ideas are valued, and doing the right thing is expected, we would love to meet you.

The company is an equal opportunity employer.

Responsibilities

We are seeking a Data Engineer to simplify and modernize our on-premises SQL Server data environment and support the transition to a corporate-managed Databricks platform. This role will redesign legacy ETL processes, build reliable ODS and DWH pipelines, and embed operational controls, data quality and governance into the engineering lifecycle.

Candidate must sit in the Jacksonville, FL office.

Key Functions/Duties of Position:

· Assess, document and rationalize existing SQL Server ETL pipelines, databases and data silos.

· Refactor redundant or fragile SQL processes into standardized, maintainable ETL/ELT pipelines.

· Design and develop ingestion, transformation and reconciliation pipelines for governed ODS and DWH environments.

· Implement logging, monitoring, error handling, auditability, lineage and repeatable deployment practices.

· Develop Databricks notebooks and pipelines using SQL and, as appropriate, Python or PySpark.

· Partner with corporate platform teams to align solutions with enterprise architecture, security and engineering standards.

· Support source-to-target mapping, testing, production support and migration validation.

• Perform other duties and/or projects as assigned

Qualifications

Education Requirement

Bachelor’s degree in Computer Science, Information Systems, Data Analytics, Data Engineering, or a related field

Qualifications: Include necessary skills/experience and core competencies required

· Strong SQL and Microsoft SQL Server development experience.

· Hands-on experience designing, building and supporting ETL/ELT pipelines.

· Knowledge of relational databases, data warehousing and incremental data processing.

· Experience troubleshooting complex data issues and reconciling source-to-target results.

· Experience with source control and disciplined software development practices.

· Strong analytical, documentation and communication skills.

Preferred Qualifications

· Databricks, Python, PySpark or Apache Spark experience.

· Experience migrating legacy ETL workloads to a cloud data platform.

· Dimensional modeling and data quality automation experience.

· Experience in a SOX-controlled or regulated environment.

· Property and casualty insurance industry knowledge, including policy, billing, claims or underwriting data, is a strong plus.

· Experience working with Guidewire applications or data, including Guidewire ClaimCenter (GWCC), Guidewire BillingCenter (GWBilling) or related policy systems.

· Experience engineering feature-ready datasets or pipelines for predictive analytics and machine learning.

· Familiarity with model lifecycle concepts, including experimentation, deployment, monitoring and reproducibility.

· Exposure to generative AI, large language models (LLMs), retrieval-augmented generation (RAG), vector search or AI-assisted data engineering.

Additional Company Details Only solicited resumes/candidate profiles that are submitted by a Berkley Preferred Agency Partner that have been requested by Berkley Internal Recruiting to engage in a particular search will be subject to the payment of Agency fees as defined in the formal agency agreement. Any unsolicited resumes/candidate profiles are not subject to payment of the agency fees. The actual salary for this position will be determined by a number of factors, including the scope, complexity and location of the role; the skills, education, training, credentials and experience of the candidate; and other conditions of employment. Sponsorship Details Sponsorship not Offered for this Role