Principal Data Architect

Mercury Insurance

Principal Data Architect managing the strategy, design, and evolution of enterprise data ecosystem. Collaborating with teams to define and execute scalable data architecture at Mercury Insurance.

Posted 6/13/2026full-timeRemote • 🇺🇸 United StatesLead💰 $107,344 - $300,603 per yearWebsite

Tech Stack

Tools & technologies

AirflowAmazon RedshiftAWSAzureBigQueryCloudGoogle Cloud PlatformInformaticaKafkaPythonSQL

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

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

ATS Keywords

✓ Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data architecturedata engineeringenterprise data platformenterprise data modelingSQLPythonInformaticadbtdata qualitycloud-native engineering

Soft Skills

leadershipmentoringstakeholder managementcommunicationarchitectural thinkinginfluencingcollaborationstrategic alignmentdelivery excellenceproblem-solving

Certifications

Bachelor's degreeMaster's degree