Principal Data Architect

Role Overview

• 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

Tech Stack

• Airflow
• Amazon Redshift
• AWS
• Azure
• BigQuery
• Cloud
• Google Cloud Platform
• Informatica
• Kafka
• Python
• SQL

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