Lead Data Engineer | P&C Insurer

Global Accounting Network is seeking a hands-on Data Engineer to join their growing data and analytics team. The Data Engineer will design, develop, and maintain modern data solutions that support business intelligence, reporting, and advanced analytics initiatives.

Responsibilities:

• Design, develop, and maintain scalable data pipelines and transformation processes within a cloud-based data platform
• Build and optimize data models that support reporting, analytics, and operational use cases
• Integrate structured and semi-structured data from a variety of source systems and third-party providers
• Develop clean, maintainable, and well-tested code while adhering to software engineering best practices
• Participate in version control, deployment processes, and automated testing methodologies
• Create and maintain technical documentation for datasets, pipelines, and data models
• Monitor and troubleshoot data workflows to ensure platform reliability, performance, and data quality
• Partner closely with analytics, reporting, and governance teams to deliver accurate and usable data products
• Support ongoing enhancements and modernization initiatives across the organization's data ecosystem
• Contribute to continuous improvement efforts, identifying opportunities to optimize data architecture and engineering processes

Requirements:

• Bachelor's degree in Computer Science, Information Systems, Engineering, Mathematics, or a related discipline, or equivalent practical experience
• Relevant cloud, data engineering, or analytics certifications are a plus
• Hands-on experience designing and supporting data engineering solutions and data pipelines
• Strong SQL skills and experience with modern data transformation frameworks
• Experience with source control systems and deployment best practices
• Understanding of data modeling concepts and data warehousing principles
• Experience working in cloud-based data environments
• Experience with modern orchestration, ingestion, and cloud data platform technologies
• Exposure to scripting or programming languages such as Python
• Familiarity with data cataloging, metadata management, or governance tools
• Experience working within insurance, financial services, or other highly regulated industries
• Understanding of modern analytics architectures and data lifecycle management