Principal Data Architect

🕒 Junho 12

🇺🇸 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 enterprise data architecture strategy, target state, and multi-year roadmap for Mercury’s data platform • Establish reference architectures, standards, and guardrails for data ingestion, transformation, modeling, orchestration, quality, observability, and consumption • Drive architecture decisions for enterprise data platforms, including EDW, lakehouse, streaming, operational data integration, and domain-oriented data products • Partner with senior Technology and business leaders to align data investments to enterprise priorities, business value, and long-term scalability • Evaluate current-state architecture, identify gaps, and lead rationalization of tools, patterns, and technical debt across the data ecosystem • Provide technical direction and architectural leadership to data engineering, analytics engineering, and platform teams • Set standards for design quality, model integrity, operational excellence, and scalable delivery across the Enterprise Data & Operations function • Mentor engineers and technical leaders in architectural thinking, modern engineering practices, and delivery excellence • Design, develop, and oversee end-to-end enterprise data solutions supporting multiple data domains, data marts, and analytics use cases • Ensure scalable batch and streaming data pipelines are built to support both enterprise reporting and advanced analytics environments • Own the reliability, quality, consistency, and observability of Mercury’s core data assets and pipelines • Define service levels and operational standards for critical data products and pipelines • Partner across Product, Engineering, Data Science, Analytics, and business teams to ensure the data platform enables real business outcomes • Lead proof of concepts, architecture reviews, and technology evaluations for new tools and capabilities

🎯 Requisitos

• Bachelor’s degree in computer science, Engineering, Information Systems, or a related field; Master’s degree preferred • 12+ years of experience in data engineering, data architecture, or enterprise data platform leadership • 5-10 years of experience leading, mentoring, and growing high-performing data engineering or analytics engineering teams • Proven experience defining enterprise data strategy and leading large-scale modernization of data pipelines, platforms, and models • Deep expertise in enterprise data modeling, including 3NF, dimensional, star, and snowflake patterns, with strong judgment on how to model real-world business processes • Strong experience redesigning foundational data models and pipelines with a focus on scalability, usability, and reliability • Expert-level SQL and Python skills, with strong production experience in Informatica and dbt, including models, testing, and package management • Experience with orchestration frameworks such as Airflow, Dagster, Tivoli, or similar tools • Familiarity with streaming and event-driven data technologies such as Kafka or comparable platforms • Hands-on experience with modern warehouse and lakehouse platforms such as Snowflake, Databricks, Redshift, or BigQuery • Strong understanding of cloud-native engineering practices across AWS, GCP, or Azure • Demonstrated commitment to engineering best practices, including Git, CI/CD, infrastructure automation, testing, and DRY design principles • Experience implementing data quality, observability, lineage, and operational controls in production environments • Strong stakeholder management and communication skills, with the ability to influence technical and non-technical leaders • Data product mindset with the ability to turn business needs into architecture, roadmaps, and execution plans • Experience in insurance, SaaS, or marketplace environments is a plus • Experience leveraging GenAI or LLM platforms such as OpenAI, Claude, or Gemini to solve meaningful business and engineering problems is strongly preferred

🏖️ 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