Data Architect

Responsibilities

• Work closely with market access, commercial, and business teams to understand key problems 
• Translate business requirements into structured data models, ontologies, and graph schemas 
• Act as a functional SME for pharma market access concepts 
• Design and implement enterprise knowledge graph solutions using Neo4j or Amazon Neptune 
• Define graph data models, including nodes, relationships, and properties aligned to business use cases 
• Build and maintain ontology frameworks capturing domain semantics and relationships 
• Ensure scalability, performance, and maintainability of graph-based architectures 
• Develop domain ontologies and taxonomies to standardize business terminology 
• Align multiple data sources into a unified semantic layer 
• Enable context-driven insights through semantic enrichment of data 
• Collaborate with data engineers and AI/ML teams to operationalize solutions 
• Ensure data quality, lineage, and governance standards 
• Establish best practices for data modeling and graph ingestion pipelines 
• Act as a key liaison between: 
  • Business teams 
  • Data engineering teams 
  • AI/analytics teams 
• Support client discussions, workshops, and solution presentations 
• Drive adoption of knowledge graph-based solutions across stakeholders 

Requirements

• Strong experience with Knowledge Graph technologies: 
• Neo4j (preferred) or Amazon Neptune 
• Proficiency in: 
  • Cypher / SPARQL / Gremlin 
  • Graph data modeling and schema design 
• Experience with: 
  • Data integration and pipeline design 
  • Graph RAG or semantic search (good to have) 
• Familiarity with cloud platforms (AWS/Azure/GCP) 
• Deep understanding of Pharma Market Access domain 
• Ability to map business processes to data structures and graph models 
• Soft Skills:
• Strong ability to translate business requirements into technical solutions 
• Excellent communication and stakeholder management skills 
• Experience working in client-facing roles and cross-functional teams 
• Problem-solving mindset with attention to detail 

Nice to have

• Prior experience in pharmaceutical analytics or consulting 
• Exposure to AI/ML and Generative AI use cases (Graph RAG, knowledge-driven AI) 
• Experience defining enterprise ontologies or semantic layers 
• Certifications in cloud or data architecture are a plus 

We offer

• Competitive compensation
• Flexible working hours
• Continuous education, mentoring, and professional development programs
• A team with an excellent tech expertise