Responsibilities
- 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
- Build an automation-first culture focused on reliability, repeatability, maintainability, and continuous improvement
- Raise the bar on technical quality, design rigor, and execution across the data engineering organization
- Design, develop, and oversee end-to-end enterprise data solutions supporting multiple data domains, data marts, and analytics use cases
- Guide the design and modernization of foundational enterprise data models, including decisions around grain, entities, relationships, conformed dimensions, and slowly changing dimensions
- Ensure scalable batch and streaming data pipelines are built to support both enterprise reporting and advanced analytics environments
- Drive implementation of layered data architecture patterns, including Bronze/Silver/Gold or equivalent logical data zones
- Partner with Engineering teams to productionize data pipelines with strong performance, resiliency, and operational supportability
- Own the reliability, quality, consistency, and observability of Mercury's core data assets and pipelines
- Establish and enforce data quality frameworks, automated testing, lineage, monitoring, alerting, and recovery processes
- Define service levels and operational standards for critical data products and pipelines
- Reduce manual processes and technical debt through standardization, automation, and disciplined platform engineering
- Partner with security, compliance, and governance stakeholders to ensure data architecture aligns with enterprise risk and control requirements
- Translate business problems into scalable data products, architecture patterns, and prioritized roadmaps
- 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
- Influence vendor selection, platform direction, and engineering standards through fact-based analysis and practical technical leadership
- Identify opportunities to apply GenAI and LLM capabilities to improve engineering productivity, data operations, governance, and insight generation
Requirements
- Bachelor's degree in computer science, Engineering, Information Systems, or a related field
- 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
Nice to Have
- Master's degree preferred
- 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
Work Arrangement
Remote (Worldwide)
Additional Information
- An in-person interview may be required during the hiring process
- 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
