Director, Data Warehouse Engineering

🕒 Setembro 11

🇺🇸 Estados Unidos – Remoto (EUA)

💵 $107.344 - $300.603 / ano

⏰ Tempo Integral

🔴 Especialista

🚰 Engenheiro de Dados

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Mercury Insurance

SiteLinkedInTodas as Vagas

5001 - 10000 funcionários

Fundada em 1962

🚘 Automotivo

💼 Consultoria

📦 Logística

Automotive • Consulting • Logistics

A Mercury Insurance é um provedor líder de produtos de seguro, focando em proteger indivíduos e seus bens com um compromisso com a privacidade e o atendimento ao cliente. A empresa opera através de agentes independentes e oferece uma variedade de serviços de seguros, incluindo seguros de automóveis, residenciais e outros produtos de seguro pessoal. A Mercury Insurance prioriza a segurança das informações pessoais e a conformidade com as leis de privacidade, garantindo que os dados dos clientes sejam manuseados com cuidado e compartilhados apenas quando necessário para o atendimento de contas ou conforme exigido por lei.

Descrição

• Define and lead the vision, roadmap, and operating model for data warehouse engineering • 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 • Establish engineering standards for reliability, performance, scalability, data quality, and maintainability • Establish SLAs, data contracts, and data quality standards with engineering and data sciences teams • Oversee end-to-end data processing solutions supporting 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 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 to execute on 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, resilience, and operational support • Champion governance, controls, and best practices to improve trust in enterprise data and reduce manual effort and technical debt • Identify opportunities to use AI and automation to improve developer productivity and accelerate delivery

🎯 Requisitos

• Minimum: 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 or equivalent combination of education and/or experience • 15+ years of experience in data engineering, data warehousing, or related disciplines, with significant experience leading high-performing engineering teams and managers • 10+ years of strong people leadership experience, including coaching leaders, building teams, setting expectations, and creating accountability • Proven success leading enterprise-scale data warehouse or lake house platforms in complex business environments • Preferred: 5 or more years of experience leading large-scale data warehouse overhauls, pipeline migrations, and performance improvement initiatives across legacy platforms and modern cloud architectures • Strong technical and strategic background evaluating platforms such as Redshift, Snowflake, Databricks, or similar technologies • Deep expertise in enterprise data architecture and data modeling • Experience with redesign and migration of foundational data pipelines and warehouse structures involving 1000s of tables, data pipelines and feeds • Mastery of 3NF, dimensional, star, and snowflake modeling patterns • Strong understanding of testing, data quality frameworks, observability, incident reduction, and service reliability • Expert-level proficiency in SQL and strong proficiency in Python • 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 practices, and scalable 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 to solve high-value operational or engineering problems • Bachelor's degree in computer science or a related field, or equivalent practical experience • Experience in insurance, SaaS, or marketplace environments is a plus

🏖️ Benefícios

• Competitive compensation • Flexibility to work from anywhere in the United States for most positions • Paid time off (vacation time, sick time, 9 paid Company holidays, volunteer hours) • Incentive bonus programs (potential for holiday bonus, referral bonus, and performance-based bonus) • Medical, dental, vision, life, and pet insurance • 401 (k) retirement savings plan with company match • Engaging work environment • Promotional opportunities • Education assistance • Professional and personal development opportunities • Company recognition program • Health and wellbeing resources, including free mental wellbeing therapy/coaching sessions, child and eldercare resources, and more