Director, Data Warehouse Engineering

🔥 19 hours ago

🏄 California – Remote

🏄 California – Remote

💵 $107.3k - $300.6k / year

⏰ Full Time

🔴 Lead

🚰 Data Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

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Mercury Insurance

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

Founded 1962

🚘 Automotive

💼 Consulting

📦 Logistics

Automotive • Consulting • Logistics

Mercury Insurance is a leading provider of insurance products, focusing on protecting individuals and their assets with a commitment to privacy and customer service. The company operates through independent agents and offers a range of insurance services including auto, home, and other personal insurance products. Mercury Insurance prioritizes the security of personal information and compliance with privacy laws, ensuring that customer data is handled with care and only shared when necessary for account servicing or as legally required.

📋 Description

• Define and lead the vision, roadmap, and operating model for data warehouse engineering • Lead multiple teams responsible for enterprise data warehouse development, data marts, core data models, and scalable data pipelines • Drive modernization of the data platform, including modeling standards, orchestration, testing, observability, and automation • Establish engineering standards for reliability, performance, scalability, data quality, and maintainability • Collaborate with engineering, technology, and data science teams to establish SLAs, data contracts, and data quality standards • Oversee end-to-end data processing solutions supporting reporting, operations, data science, and AI use cases • Partner with senior leaders to align investments, priorities, and delivery plans • Translate business goals into data platform capabilities, roadmaps, and measurable outcomes • Lead the evolution of enterprise data models, including grain, entities, relationships, conformed dimensions, and slowly changing dimensions • Drive a data product mindset and scalable, reusable data capabilities • Build an engineering culture focused on ownership, continuous improvement, automation, and disciplined execution • Mentor and develop managers, senior engineers, and technical leads • Build and manage multiple teams executing the data strategy • Guide capacity planning, prioritization, vendor and tool decisions, and resource allocation • Partner with engineering teams to productionize pipelines and integrations with strong service levels and resilience • Champion governance, controls, and best practices to improve data trust and reduce manual effort and technical debt • Identify AI and automation opportunities to improve productivity and accelerate delivery

🎯 Requirements

• Bachelor's degree in Data Science, Data Engineering, Computer Science, Mathematics, Statistics, Engineering, Information Systems, Business Administration, or related technical field • Master's degree preferred • 15+ years of experience in data engineering, data warehousing, or related disciplines • 10+ years of people leadership experience, including coaching leaders, building teams, setting expectations, and creating accountability • Proven success leading enterprise-scale data warehouse or lakehouse platforms in complex business environments • Deep expertise in enterprise data architecture and data modeling • Experience redesigning and migrating foundational data pipelines and warehouse structures involving thousands of tables, data pipelines, and feeds • Experience partnering with cross-functional stakeholders and senior leaders to prioritize roadmaps, resolve trade-offs, and deliver business value • Experience leading production support for EDS and mandatory data requirements • Mastery of 3NF, dimensional, star, and snowflake modeling patterns • Strong understanding of testing, data quality frameworks, observability, incident reduction, and service reliability • Expert-level SQL proficiency and strong Python proficiency • Production experience with Informatica, DBT, Airflow, Tivoli, Dagster, and Git-based development workflows • Hands-on experience with Redshift, Databricks, Snowflake, or BigQuery • Familiarity with layered (medallion) data architecture patterns • Strong experience with CI/CD, automation-first engineering, and scalable cloud software delivery in AWS, GCP, or Azure • Strong communication skills with the ability to influence technical and non-technical audiences without authority • Experience using OpenAI, Claude, or Gemini for operational or engineering problems • Bachelor's degree in computer science or related field, or equivalent practical experience • Experience in insurance, SaaS, or marketplace environments is a plus

🏖️ Benefits

• Lead a high-impact function that shapes Mercury’s enterprise data foundation • Work across Engineering, Data Science, and business teams on visible initiatives with meaningful enterprise reach • Build and grow a strong organization while raising the bar on architecture, delivery, and operational excellence