Dir Data Warehouse Engineering

Position Summary

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.

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.

Essential Job Functions:

• 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.
• Build a strong engineering culture grounded in ownership, continuous improvement, automation, and disciplined execution.
• Mentor and develop managers, senior engineers, and technical leads, while strengthening succession planning and organizational capability.
• Build and manage multiple teams to execute on establishing data strategy.
• Guide to capacity planning, prioritization, vendor and tool decisions, and resource allocation across the function.
• Partner with engineering teams to product ionize pipelines and integrations with strong service levels, resilience, and operational support.
• Champion governance, controls, and best practices that improve trust in enterprise data and reduce manual effort and technical debt.
• Identify opportunities to use AI and automation to improve developer productivity, reduce repetitive work, and accelerate delivery.

• Bachelor's degree in Data Science, Data Engineering, Computer Science, Mathematics, Statistics, Engineering, Information Systems, Business…