Data Engineer - ETL

Berkley • Jacksonville, FL

1d • Onsite

About The Position

Carolina Casualty is seeking a Data Engineer to simplify and modernize its on-premises SQL Server data environment and support the transition to a corporate-managed Databricks platform. The role will redesign legacy ETL processes, build reliable operational data store (ODS) and data warehouse (DWH) pipelines, and incorporate operational controls, data quality, and governance into the engineering lifecycle. The candidate must work from the Jacksonville, Florida office.

Carolina Casualty specializes in liability, physical damage, cargo, and other insurance solutions for commercial auto markets, including trucking and public transportation. It is a member of W. R. Berkley Corporation. The company emphasizes integrity, valuing each person's contributions, and responsible innovation, and is an equal opportunity employer.

Requirements

• Bachelor’s degree in Computer Science, Information Systems, Data Analytics, Data Engineering, or a related field.
• 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.
• Must sit in the Jacksonville, Florida office.

Nice To Haves

• 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.
• 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.

Responsibilities

• 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.

What This Job Offers

• Job Type: Full-time