Data Engineering Practice Lead: AI-Ready Platform

Core Specialty Insurance Holdings, Inc.; Cincinnati (OH); On-site; USD 120,000 - 180,000; Full time

Job summary

Core Specialty Insurance Holdings, Inc. is seeking a hands-on Data Engineer in Cincinnati or Dallas to lead the continued optimization of our large-scale data platform. You will act as a working solution architect—roughly 60% of your time—shaping architecture, scaling pipelines, and ensuring AI/ML readiness for the business.

The remaining 40% focuses on strategy, direction, and team leadership. Reporting to the VP-Data Engineering, AI & ML, you will guide a team of Data Engineers, set technical

Qualifications

• Bachelor's degree in Computer Science or related field or equivalent work experience.
• Minimum 10+ years in data engineering with large-scale platforms.
• 3+ years in architect roles with direct ownership of solution designs.
• 3+ years leading data engineering teams with people management.

Responsibilities

• Own the technical evolution of a large-scale data platform, improving architecture and scalability.
• Lead data engineering initiatives as the primary solution architect.
• Design, prototype, and develop platform components for high-risk initiatives.
• Drive AI/ML readiness and governance as data usage grows.
• Collaborate on tooling selection (storage, orchestration, compute, streaming).
• Mentor and manage data engineers; guide roadmap and budgeting.

Skills

Data pipeline design

Distributed processing

Python

SQL

Scala

Cloud platforms

Leadership

Governance & security

Education

Bachelor Degree in Computer Science or related field

Tools

Snowflake

Databricks

Azure Synapse Analytics

MS Fabric

Terraform

GitHub Actions

Delta Lake

Iceberg

Job description

Core Specialty Insurance Holdings, Inc. is seeking a hands-on Data Engineer in Cincinnati or Dallas to lead the continued optimization of our large-scale data platform. You will act as a working solution architect—roughly 60% of your time—shaping architecture, scaling pipelines, and ensuring AI/ML readiness for the business.

The remaining 40% focuses on strategy, direction, and team leadership. Reporting to the VP-Data Engineering, AI & ML, you will guide a team of Data Engineers, set technical