Director, Data Engineering – AI/ML Platform Leader

Kalepa Insurance Services, LLC; Cincinnati (OH); Hybrid; USD 180,000 - 260,000; Full time

Benefits offered by this job

Medical, dental, vision

Life insurance

Short/long-term disability

401(k) company match 100% of 6%

Employee Assistance Plan

Health Savings Account

Flexible Spending Account

Wellness program

Job summary

Core Specialty is seeking a Director of Data Engineering in Cincinnati to lead a large-scale data platform. This hands-on role combines solution architecture (about 60%) with leadership to guide the Data Engineering team, ensuring scalability, security, and AI/ML readiness across the organization.

You will design data pipelines, evaluate tooling like Snowflake, Databricks, and Azure Synapse, and mentor engineers while aligning with enterprise architecture to set technical standards and roadmap

Qualifications

• 12+ years in data engineering focusing on large-scale platforms.
• 3+ years in architect roles with ownership of solution designs.
• 3+ years in leadership managing data engineering teams.

Responsibilities

• Own the technical evolution of our data platform, driving architecture improvements and scalability.
• Act as lead solution architect for data engineering initiatives and high-complexity projects.
• Design and prototype frameworks and platform components for high-risk initiatives.
• Ensure AI/ML readiness and governance across the data platform.

Skills

Data pipeline design

Distributed data processing

Python/Scala/SQL

Cloud data platforms

Snowflake/Databricks

Terraform

GitHub Actions

Tools

Snowflake

Databricks

Azure Synapse Analytics

Terraform

GitHub Actions

Job description

Core Specialty is seeking a Director of Data Engineering in Cincinnati to lead a large-scale data platform. This hands-on role combines solution architecture (about 60%) with leadership to guide the Data Engineering team, ensuring scalability, security, and AI/ML readiness across the organization.

You will design data pipelines, evaluate tooling like Snowflake, Databricks, and Azure Synapse, and mentor engineers while aligning with enterprise architecture to set technical standards and roadmap