Key Responsibilities
Data Engineering
Design, develop, and maintain scalable data pipelines, data models, and data products across enterprise platforms.
Integrate structured and unstructured data from multiple business systems and sources.
Build and optimize data architectures that support analytics, reporting, AI applications, and knowledge management initiatives.
Ensure data quality, reliability, governance, and performance across enterprise data assets.
Collaborate with business stakeholders to translate business requirements into scalable technical solutions.
Enterprise Knowledge Base Development
Lead the design, implementation, and continuous improvement of enterprise knowledge base solutions.
Identify, organize, structure, and maintain business knowledge assets to improve discoverability and reuse.
Develop frameworks and processes for transforming business knowledge into scalable enterprise resources.
Partner with business, commercial, digital, and AI teams to establish sustainable knowledge management practices.
Drive knowledge governance, content organization, metadata management, and knowledge lifecycle management.
AI & Knowledge Enablement
Evaluate how emerging AI technologies, including Large Language Models (LLMs), impact enterprise knowledge management strategies.
Support AI-powered business initiatives by providing high-quality knowledge foundations and structured information assets.
Stay current with industry trends and best practices in enterprise knowledge management, AI, and information architecture.
Provide recommendations on future-state knowledge platform capabilities and enterprise knowledge strategies.
Required Qualifications
Bachelor's degree or above in Computer Science, Data Engineering, Information Systems, Data Science, or a related field.
3+ years of experience in Data Engineering, Data Platform, or related technical roles.
At least 2 years of recent hands-on experience designing, implementing, and maintaining enterprise knowledge base or knowledge management solutions.
Strong experience in data modeling, data integration, ETL/ELT development, and enterprise data architecture.
Proficiency in SQL and modern data engineering technologies.
Experience working with both structured and unstructured data.
Strong understanding of enterprise knowledge management concepts, methodologies, and best practices.
Familiarity with current AI and LLM developments and their impact on enterprise knowledge management.
Ability to articulate perspectives on the evolution, current state, and future direction of enterprise knowledge platforms.
Strong problem-solving, communication, and stakeholder management skills.
Demonstrated ability to work in fast-paced, rapidly evolving environments.
Preferred Qualifications
Experience supporting AI-enabled business applications, digital transformation, or enterprise search initiatives.
Experience with knowledge graphs, semantic search, enterprise search platforms, content management systems, or related technologies.
Experience working with cloud-based data platforms (Databricks, Azure, AWS).
Familiarity with data governance, master data management, and enterprise information architecture.
Experience in the pharmaceutical, biotechnology, healthcare, or life sciences industry will be preferred.
Experience collaborating with commercial, marketing, customer experience, or digital teams.
Key Success Factors
Strong ownership and execution mindset.
Ability to quickly learn new technologies and business domains.
Excellent collaboration skills with cross-functional teams.
Curiosity and passion for emerging technologies and AI innovation.
Comfortable working in an agile, fast-changing, and iterative environment.
