Data & Information Architect

Role Description

Roles & Responsibilities

• Design, develop, and deploy connected data solutions using Information Modeling, Knowledge Graphs, and Generative AI, to address high-value business and operational challenges.
• Build intelligent solutions that combine structured and unstructured data , semantic data models, and knowledge graph capabilities to improve automation, search, insight generation, and decision support.
• Develop and scale proof-of-concept solutions in SQL and SPARQL and transition them into robust, enterprise-ready Data products for broader organizational use.
• Apply SQL , R2RML , and other data transformation techniques to analyze, integrate, and prepare data from multiple enterprise sources.
• Collaborate with business stakeholders, product teams, data engineers, architects, and domain experts to identify Data use cases and translate business requirements into scalable technical solutions.
• Integrate FAIR data principles and data-centric design practices with AI to promote interoperability, discoverability, and governance of data assets.
• Utilize Databricks and associated data/AI workflows to support experimentation, and model verification with real world data
• Ensure alignment with Responsible AI , security, privacy, and compliance expectations, including familiarity with emerging AI regulatory frameworks such as the EU AI Act .
• Facilitate working sessions with stakeholders to clarify concepts, define success criteria, and align on transformation opportunities enabled by Data.
• Contribute to the development of standards, reusable data products, and best practices for Model-driven design, semantic modeling, and product scaling.
• Promote a culture of continuous improvement , innovation, and transformation by identifying opportunities to improve current processes, technologies, and ways of working.
• Stay current with advancements in Knowledge Graphs , context engineering, agentic architectures, and regulatory expectations, and apply those insights pragmatically within the organization.

Basic Qualifications and Experience

• Doctorate Degree OR
• Master’s or Bachelor’s degree with 5 to 8 years of experience in Data Science, Artificial Intelligence, Computer Science, Information Science, or related field

Must-Have Skills

• Strong hands-on experience in Information Modeling, Knowledge Graph development, and Generative AI, concepts and applications.
• Proficiency in knowledge elicitation, data modeling for rapid prototyping, solution development, and scaling AI-driven capabilities.
• Strong working knowledge of SQL for data analysis, transformation, and integration across enterprise systems.
• Hands-on experience with Databricks or comparable data and AI platforms.
• Strong understanding of integrated data, enterprise data ecosystems, and data-centric solution design.
• Experience with knowledge graph and graph-based data platforms such as Stardog, GraphDB , or similar technologies.
• Strong understanding of FAIR data principles and their application in enterprise and pharmaceutical data environments.
• Ability to translate business concepts and requirements into models, semantic concepts, and data solutions.

Good-to-Have Skills

• Experience with regulatory data , regulatory submission processes, or compliance requirements in the pharmaceutical domain.
• Familiarity with the pharmaceutical lifecycle of data , including development, manufacturing, regulatory, and operational domains.
• Knowledge of data modeling and knowledge graph concepts.
• Experience integrating data from sources such as clinical, laboratory, manufacturing, quality, or regulatory systems.
• Familiarity with healthcare and life sciences standards such as FHIR , IDMP , or related interoperability frameworks.
• Familiarity with product-oriented delivery and scaling data proofs of concept into operationalized enterprise capabilities.

Soft Skills

• Exceptional interpersonal, communication , facilitation, and business analysis skills.
• Strong analytical thinking and structured problem-solving skills, especially in complex and regulated environments.
• Ability to manage ambiguity, think strategically, and convert emerging opportunities into practical solutions.
• Strong ability to prioritize and manage multiple initiatives in a dynamic setting.
• Demonstrated customer- and user-centric product design mindset.
• Strong collaboration skills with cross-functional, global, and multidisciplinary teams.
• Ability to influence without authority and build alignment across technical and business stakeholders.
• Passion for continuous improvement , innovation, and transformation.
• Strong ownership mindset with the ability to independently drive high-impact work from concept through implementation.

EQUAL OPPORTUNITY STATEMENT