Data Engineer - ETL

Required Skills & Experience

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.

Nice to Have Skills & Experience

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.

Job Description

We are seeking a Senior 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.

pay ranges from $60-68/hr based on years of experience