Data Warehouse Principal Architect

Role Summary

Immunome is seeking an experienced Data Warehouse Principal Architect to define the end-to-end architecture and deployment of the enterprise data warehouse and analytics platform. You will manage the technical scope, data strategy, data ingestion, delivery roadmap, and partner with stakeholders on reporting and consumption needs. Phase one focuses on commercial readiness, enabling rapid integration and trusted reporting from key enterprise systems and external data sources. You will initially be a sole contributor, leading external consultants and implementation partners while collaborating with the IT platform team, cybersecurity, technical and business analysts, business leadership, and executives; reporting to the Senior Director, Business Systems.

Responsibilities

• Enterprise & Solution Architecture
  • Define and maintain the enterprise data architecture roadmap aligned with business and technology strategy.
  • Develop reference architectures, design patterns, and reusable components for data ingestion, transformation, modeling, and analytics.
  • Define enterprise standards and governance.
• Data Warehouse & Analytics Architecture
  • Lead the design and deployment of enterprise data warehouse and analytics solutions.
  • Architect systems that support analytical, operational, and regulatory workloads using both batch and real-time data patterns.
  • Define and create semantic, logical, and physical data models to support scalable analytics and self-service consumption.
  • Define and implement production operating practices including monitoring, alerting, data observability, performance management, cost management, access controls, and service level expectations for data availability and quality.
• Master Data Management & Data Governance
  • Define and support master and reference data strategies to ensure consistency of critical enterprise data.
  • Embed data quality, metadata, and lineage considerations into all architectural designs.
  • Partner with governance and stewardship functions to enforce data ownership, classification, and privacy controls.
• AI / Advanced Analytics Enablement
  • Architect data environments that are analytics- and AI-ready, supporting feature engineering, reproducibility, and trustworthy downstream consumption.
  • Partner with analytics and data science teams to ensure architectural alignment with advanced analytics use cases.
• Cross-Domain Collaboration
  • Lead cross functional initiatives and working sessions to define priorities, clarify requirements, resolve tradeoffs, and drive timely decisions across stakeholders.
  • Lead external consultants, system integrators, and vendors by defining scope, setting deliverables, reviewing work products, and ensuring solutions meet architectural standards and business outcomes.
  • Prioritize and deliver foundational commercial readiness data capabilities, including reliable integration of key commercial and enterprise data sources and scalable metric definitions to support reporting and operational workflows.
  • Define and evolve the data platform operating model, including support processes, documentation standards, and a scaling plan for additional capabilities, internal roles, and partner support as adoption grows.

Qualifications

• A minimum of 10+ years’ experience in data warehouse architecture, development, or design.
• Expertise in data architecture, data modeling, and analytics system design.
• Strong understanding of batch vs. real-time data patterns and distributed data processing concepts.
• Demonstrated success implementing and/or owning production data platforms as a senior individual contributor.
• Excellent communication skills with the ability to influence technical and business stakeholders.

Education

• Bachelor’s degree in Computer Science, Data Engineering, Information Systems, or a related field required; advanced degrees or relevant technical certifications preferred.

Knowledge And Skills

• Experience designing enterprise-wide data architecture standards and governance frameworks.
• Experience with ML and AI for training system models and/or mastering unstructured data – as well as other use cases.
• Experience designing data platforms that support audit readiness, privacy controls, and regulated requirements such as FDA GxP and 21 CFR Part 11, as well as supporting internal controls expectations for public company environments.
• Experience operating in dynamic, fast-growing enterprise environments.
• Strategic thinker capable of translating architecture into measurable business outcomes.
• Strong influencer who can align stakeholders across federated teams without direct authority.
• Pragmatic, collaborative, and comfortable mentoring engineers and architects across the organization.
• Able to operate effectively across multiple business units and priorities.