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Precision for Medicine is building the Data Hub, a centralized data platform consolidating legacy infrastructure, establishing enterprise-grade data foundations, and enabling advanced analytics and AI capabilities across the organization.
The Principal Data Engineer is a senior technical leader and hands-on contributor responsible for designing, implementing, optimizing, and operating the Data Hub's core platform capabilities. This role spans data engineering, platform engineering, DevOps, architecture, and data governance. You will define technical direction while remaining actively involved in solution design, infrastructure building, code review, production troubleshooting, and engineering practice improvement.
This is not a management role. While you will mentor and guide junior engineers, analytics engineers, and platform contributors, you will have no direct reports. The ideal candidate enjoys solving complex technical challenges, setting high engineering standards, and leading through expertise and influence rather than organizational hierarchy.
Key responsibilities include:
**Infrastructure & Platform Engineering**: Design and maintain scalable, secure, cloud-native data platform infrastructure. Develop infrastructure-as-code, CI/CD pipelines, deployment automation, and environment management. Partner with Corporate IT and Security for compliance and operational excellence. Improve observability through monitoring, alerting, and performance tracking.
**Data Architecture & Modeling**: Design scalable data models supporting analytics, reporting, AI/ML, and operational use cases. Define and evolve architecture standards and best practices. Ensure solutions align with governance, lineage, security, and regulatory requirements. Guide teams in implementing maintainable data structures.
**Data Engineering & Solution Delivery**: Build and optimize data ingestion, transformation, and delivery pipelines across business domains. Lead technical design reviews and contribute to complex initiatives. Collaborate with Product, Analytics, AI/ML, and business stakeholders. Provide hands-on support for critical initiatives and modernization programs.
**DevOps & Engineering Excellence**: Establish software engineering, GitOps, DevOps, testing, and deployment standards. Drive automation across development, deployment, and operations. Promote best practices for code quality, documentation, and technical debt management. Conduct architecture and code reviews.
**Quality, Performance & Reliability**: Identify and resolve performance bottlenecks. Define and implement data quality frameworks and automated validation. Optimize platform cost, scalability, and efficiency. Lead root-cause analysis for production incidents.
**Technical Leadership & Mentorship**: Mentor Data Engineers and Analytics Engineers through coaching, code review, and design guidance. Act as trusted technical advisor across teams. Share knowledge and promote continuous improvement.
**Strategic Planning**: Participate in Data Hub leadership activities including roadmap planning, technology evaluation, and executive reporting. Provide technical recommendations on platform investments and architecture direction. Collaborate with Product Management, AI/ML teams, and business stakeholders.
