Data Engineering Director - Hybrid

About the role

National Interstate, a member of Great American Insurance Group, is seeking a Data Engineering Director to lead its data engineering team. This role is hybrid, requiring on-site presence in the Richfield, OH office three days per week (typically Tuesday, Wednesday, and Thursday), with flexibility determined by business needs. The position focuses on enhancing workflow efficiency, strategic planning, and fostering collaboration across business units to align data initiatives with organizational goals.

Responsibilities

• Oversee Data Engineering team operations, workflow efficiency, and productivity.
• Lead strategic planning and execution to align data engineering initiatives with organizational goals and innovation.
• Design, develop, and optimize data pipelines and architectures for integration, storage, and retrieval.
• Provide leadership and guidance on ETL processes to ensure seamless data flow and high data quality standards.
• Collaborate with business analysts, project managers, and stakeholders to translate business needs into technical requirements and provide project updates.
• Drive adoption of cutting-edge technologies to enhance operational performance, scalability, and resilience.
• Mentor team members, promote best practices, and foster a culture of continuous improvement.
• Evaluate and implement industry-leading best practices to maintain a competitive edge and drive technological advancements.
• Perform other duties as assigned.

Strategic Business Leadership & Domain Expertise

• Experience with data strategy for P&C insurance business domains, including Underwriting, Claims, Operations, Finance, and Customer Experience.
• Lead enterprise digital transformation by establishing foundational data governance practices, operational data stores, and advanced analytics capabilities.
• Collaborate with C-suite executives and business unit leaders to translate strategic business goals into actionable data roadmaps, balancing priorities across business demand, technology modernization, and regulatory compliance.
• Champion data product development to create reusable, trusted data assets that power analytics, reporting, and business intelligence across multiple business domains.

End-to-End Data Ecosystem Architecture

• Design and implement an enterprise data ecosystem spanning data capture at source systems through to consumption.
• Design and architect enterprise data assets such as Operational Data Store (ODS).
• Architect scalable ETL/ELT pipelines across batch, real-time, and event-driven latencies.
• Familiarity with warehousing solutions using Snowflake and Informatica Data Management Cloud (IDMC) to serve as a single source of truth for enterprise reporting and advanced analytics.

Data Governance & Compliance Leadership

• Develop a comprehensive data catalog and Data Quality (DQ) framework with data lineage, quality scoring, and control documentation.
• Design and implement error and audit logging frameworks across ETL and integration pipelines to support traceability, root-cause analysis, and audit/compliance requirements.
• Establish data governance frameworks and data catalog tools to improve data quality, consistency, and regulatory compliance across all business domains.
• Define and enforce data architecture policies governing data collection, integration, storage, and usage to align with strategic business goals and regulatory requirements (e.g., HIPAA, state insurance regulations).
• Lead data stewardship programs across business units, establishing data ownership models and accountability frameworks.

Requirements

• Bachelor’s degree in Information Technology, Computer Science, Software Engineering, or a related field.
• Minimum of 18 years of experience in data engineering or a related field, including at least 8 years of leadership experience.
• Experience with data warehousing solutions and ETL processes.
• Typically manages 2 or more reports and contributes to strategy, performance targets, and policies/procedures.
• Expert proficiency in multiple programming languages, cloud platforms, and modern development frameworks.
• Expert consultancy on business and technology operations.
• Expert understanding of machine learning concepts and their software engineering implications.
• Maintains expert knowledge of industry trends and technologies to continuously improve data engineering solutions.
• Responsible for managing staff performance, talent selection, development, and performance management.
• Plans and ensures the team meets budget and performance targets.
• Proficiency in SQL and experience with relational database management systems (e.g., MySQL, PostgreSQL, Oracle).
• Knowledge of data modeling, data architecture, and data governance.
• Familiarity with big data technologies (e.g., Hadoop, Spark) is a plus.

Benefits

• Full-time employees have access to medical, dental, and vision coverage, wellness plans, parental leave, adoption assistance, and tuition reimbursement.
• Full-time and eligible part-time employees enjoy Paid Time Off and paid holidays, a 401(k) plan with company match, an employee stock purchase plan, and commuter benefits.