Dir Data Warehouse Engineering - Mercury Insurance Company

Mercury Insurance is looking for a Director, Data Warehouse Engineering to lead the strategy, architecture, and delivery of our enterprise data warehouse platform. This leader will own the direction of the data warehouse engineering function and help modernize the way data is built, governed, and delivered across the company.

This role combines people leadership, architectural depth, and operational excellence. You will lead teams that build and support scalable EDW data platforms, enterprise data models, and high-reliability pipelines that serve analytics, reporting, operational use cases, and AI-enabled solutions. You will partner closely with Engineering, Data Science, Product, and business stakeholders to ensure Mercury’s data foundation is trusted, scalable, and aligned with business priorities.

The ideal candidate brings strong experience leading data warehousing and data engineering organizations, modernizing enterprise data platforms, and driving execution across a complex environment. This is a highly visible leadership role for someone who can set vision, raise engineering standards, and develop high-performing teams while staying connected to the technical details that matter.

• Define and lead the vision, roadmap, and operating model for data warehouse engineering in support of Mercury’s enterprise data strategy.
• Lead multiple teams or a broader engineering function responsible for enterprise data warehouse development, data marts, core data models, and scalable data pipelines.
• Drive modernization of the data platform, including data modeling standards, orchestration patterns, testing frameworks, observability, and automation to optimize efficiency.
• Establish engineering standards for reliability, performance, scalability, data quality, and maintainability across the warehouse and pipeline ecosystem.
• Cross-collaborate with engineering/technology and data sciences teams to establish SLAs, data contracts, and data quality standards.
• Oversee the design and implementation of end-to-end data processing solutions that support enterprise reporting, business operations, data science, and AI use cases.
• Partner with senior leaders across Engineering, Data Science, Architecture, and business teams to align investments, priorities, and delivery plans.
• Translate business goals into a clear portfolio of data platform capabilities, delivery of roadmaps, and measurable outcomes.
• Lead the evolution of enterprise data models, including decisions on grain, entities, relationships, conformed dimensions, and slowly changing dimensions.
• Drive a data product mindset across the organization, helping teams move from reactive ticket-based delivery to scalable, reusable data capabilities.