Data Engineering Practice Lead

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

Cincinnati or Dallas (not a remote position)

We are looking for a Data Engineer, to lead the continued optimization and maturation of our existing large-scale data platform. This is hands-on technical leadership role: roughly 60% of your time will be spent as a working solution architect – improving, rearchitecting, and scaling data pipelines, infrastructure, and models that power the business. The remaining 40% will be focused on strategic alignment, technical direction, and resource management for the Data Engineering team. A key part of the mandate is ensuring the platform remains AI/ML ready as it scales – well modeled and well governed so that advanced analytics teams can reliably and efficiently access high-quality data. Data Vault 2.0 or Ensemble data modeling techniques is preferred.

Reporting to the VP-Data Engineering, AI & ML, you will lead a team of Data Engineers – setting the technical execution direction while staying close enough to the architecture and code to guide hard decision, unblock the team, and ensure the platform continues to scale reliably and security as usage and AI/ML initiatives grow.

Applicants must be authorized to work for any employer in the U.S. We are unable to sponsor or take over work authorization sponsorship now or in the future for this position.

• Own the technical evolution of our existing large-scale data platform, identifying and riving improvements to architecture, performance and scalability data volume and complexity use cases grow
• Act as the lead solution architect for data engineering initiatives
• Personally design, prototype, and development of frameworks and critical platform components – especially for high-risk/high complexity initiatives
• Have a forward-thinking posture as it comes to creating an AI/ML ready data platform
• Participate in the evaluation, selection and implementation of data platform tooling (i.e. – storage, orchestration, compute, streaming)
• Reinforce existing data observability solutions/standards across pipelines and the platform
• Diagnose and resolve complex production issues/technical debt across the data platform – partnering directly with other engineers to resolve.

Strategy, Technical Direction & Resource Management

• Partner with VP-Data Engineering, AI & ML to define and execute the roadmap for a fully optimized and scalable data platform – ensuring alignment to broader company and data strategies including AI/ML readiness assessments
• Set technical direction and architectural standards for the team by working closely with Enterprise Architecture
• Manage, mentor, and develop data engineers
• Participate in resource planning and prioritization across the team’s product roadmap – balancing business requests with platform-based initiatives
• Represent Data Engineering planning, budgeting, and resource management discussions as needed
• Stay current with emerging trends in data engineering and data platform architecture – brining innovations into continued data maturity for the organization.

Technical Knowledge and Understanding:

Technical Knowledge

• Deep expertise in data pipeline design, optimization, and distributed data processing architectures with experience identifying and resolving performance and scalability bottlenecks
• Platforms: Hands on experience with Snowflake or Databricks (experience in an architecture role with these platforms is a plus), Azure Synapse Analytics/MS Fabric
• Strong knowledge of cloud data platforms (AWS, Azure, or GCP) and modern data warehouse/Lakehouse architectures (Delta Lake, Iceberg)
• Working familiarity with AI/ML data requirements and tooling to support AI/ML enablement
• Strong working proficiency with at least two programming languages (Python, Scala, SQL)
• Solid understanding of data governance, security, and compliance practices in a regulated or enterprise environment
• Experience with IAC and CI/CD practices for data systems (i.e. Terraform, GitHub Actions)

Leadership & Soft Skills

• Proven ability to set technical direction while remaining hands-on and credible at the architecture and code level
• Strong stakeholder management skills – the ability to translate between technical and non-technical audiences
• Excellent prioritization and resource management skills across competing technical and business demands
• A coaching mindset with genuine investment in growing the technical and soft skills of direct reports

Requirements:

• Bachelor Degree in Computer Science or related field or equivalent work experience.
• 10+ years experience in data engineering with significant experience in optimizing, scaling, and evolving large-scale mature data platforms
• 3+ years in an architect role (Solution, Enterprise, Data, Platform) with direct ownership of solution designs
• 3+ years in a leadership role managing data engineering teams – including direct people management responsibilities
• Working knowledge of how data platforms enable AI/ML solutions
• Track record of balancing hands-on technical delivery with people leadership and strategic planning

Nice to Have

• Experience designing or implementing Agentic workflows for data engineering
• Experience working with Property & Casualty insurance carriers
• Experience with Data Vault 2.0 or Ensemble data modeling techniques