Principal Data Architect

🔥 0 minutes ago

🇺🇸 United States – Remote

💵 $107.3k - $300.6k / year

⏰ Full Time

🔴 Lead

🚰 Data Engineer

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Mercury Insurance

WebsiteLinkedInAll Job Openings

5001 - 10000 employees

Founded 1962

💸 Finance

👥 B2C

Insurance • Finance • B2C

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 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

🎯 Requirements

• 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

🏖️ Benefits

• 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