Product Data Architect - Evinova

WHY JOIN US? Evinova is a health-tech business focused on accelerating better health outcomes by advancing digital transformation across the life sciences sector. By combining science-based expertise, evidence-led rigor, and deep human insight, we design digital solutions that enable healthcare to work better for everyone. Operating at the intersection of healthcare, technology, data, and analytics, we are helping unlock the full potential of digital health, transforming how clinical research is conducted, how care is delivered, and how patients experience healthcare. Our solutions are built to scale, driving efficiency, improving decision-making, and ultimately delivering better outcomes for patients worldwide. At Evinova, we are driven by a shared purpose to transform health through data and digital innovation. Our teams collaborate across disciplines to solve complex challenges, continuously learning and evolving in a fast-paced, high-impact environment. We also recognize the importance of flexibility and balance. Our ways of working support both individual needs and team collaboration. To foster connection and collaboration, employees are expected to work from the office three days per week, creating opportunities for in-person teamwork, innovation, and meaningful connection. Role Summary: As a Product Data Architect at Evinova, you will shape the data architecture behind our AI-powered products, including Study Designer and AI Document Authoring. You’ll design scalable, secure, and high-quality data solutions that enable smarter, more connected clinical trials. Working closely with Product and Engineering teams, you’ll define data models, integration patterns, and standards that support both current delivery and future innovation—especially across AI, LLM, and RAG-driven capabilities in a regulated environment. This is a high-impact role where you’ll help build the data foundations that power the next generation of digital health solutions. What You’ll Do: Shape Data Architecture for AI-Powered Products Design and evolve data models that power our AI-native products Build and guide architectures supporting LLMs, generative AI, and RAG pipelines Define scalable data flows, integration patterns, and interfaces across products Establish reusable data patterns to support long-term product growth Ensure Quality, Compliance, and Scalability Drive consistency and interoperability across our product ecosystem Align data architecture with regulatory and enterprise standards (including GxP) Support data governance practices like access, retention, and auditability Identify risks and continuously improve data architecture and performance Use Data to Drive Better Decisions Define metrics and dashboards to monitor data quality and system health Turn insights into actionable improvements for product and engineering teams Promote a strong data quality mindset across teams Collaborate and Deliver Across Teams Partner with Product and Engineering to bring scalable data solutions to life Work closely with global teams and external partners to guide implementation Stay hands-on when needed—supporting design, troubleshooting, and delivery Lead and Elevate Data Excellence Mentor engineers and help set best practices for data architecture Contribute to a shared vision across teams and geographies Help define how data supports AI-driven product innovation at scale What Success Looks Like: Data models and interfaces are clear, scalable, and widely adopted across teams Product teams move faster with fewer data-related blockers or rework Data architecture evolves seamlessly as products, AI capabilities, and usage grow LLM and RAG pipelines are reliable, transparent, and meet both technical and regulatory standards You are seen as a trusted partner by Product and Engineering leadership Required Qualifications Bachelor's degree in Computer Science, Computer Engineering, Mathematics, Information Science, or a related field 8+ years of experience in data architecture, data engineering, or platform architecture roles Proven experience owning data architecture for complex products or product suites Strong experience in data modeling and data design Proficiency in Python Experience working with SQL and NoSQL databases Hands-on experience building and managing ETL processes and data pipelines Demonstrated ability to make architectural decisions with product-level impact Strong collaboration skills with Product and Engineering teams A data-driven mindset, with experience defining metrics and using insights to guide decisions Preferred Qualifications Experience architecting data layers for AI/ML-powered products — especially LLM pipelines, RAG architectures, vector databases, or embedding strategies. Familiarity with GxP software validation, computerised system validation (CSV), or regulated-industry quality practices. Background in life sciences, health-tech, or clinical-trial technology. Experience working with geographically distributed teams and external vendor squads. Experience operating within a Data Owner / Data Steward governance model. Experience defining reference architectures reused across multiple products. Prior experience mentoring senior engineers or architects. SO, WHAT’S NEXT? To be considered for this exciting opportunity, please complete the full application on our website at your earliest convenience – it is the only way that our Recruiter and Hiring Manager can know that you feel well qualified for this opportunity.  If you know someone who would be a great fit, please share this posting with them. Where can I find out more? Explore what we’re building: www.evinova.com Stay connected and see our impact in action: https://www.linkedin.com/company/evinova/ Apply today to bring smarter, faster clinical trials to life! Evinova is an equal opportunity employer that is commi