Principal Knowledge Graph Engineer, Drug Discovery Data Engineering and Solutions

$135,000 - $202,000/Yr

Johnson & Johnson - San Diego, CA

Full-time - Principal

Remote - San Diego, CA

Chemical Manufacturing

About the position

J&J Innovative Medicine (J&J IM), a Johnson & Johnson company, is seeking a Principal Knowledge Graph Engineer to join the Drug Discovery Data Engineering and Solutions team. This position is pivotal in architecting, building, and maintaining a sophisticated knowledge graph infrastructure that integrates diverse biomedical data sources to support drug discovery, personalized medicine, and advanced research initiatives. The primary location for this position is flexible, with options including Titusville, NJ; Spring House, PA; San Diego, CA; and Boston, MA, with considerations for alternate locations and remote work. J&J Innovative Medicine is dedicated to developing treatments that enhance the health and lifestyles of people worldwide, focusing on areas such as Oncology, Immunology, Neuroscience, and Cardiovascular, Metabolism & Retina. The ultimate goal is to help people live longer, healthier lives by producing and marketing first-in-class prescription medications that meet the broad needs of the healthcare market. The Data Science Solutions, Privacy & Ethics team is part of J&J Innovative Medicine's Data Science and Digital Health department. This team is committed to using innovative technology to improve healthcare outcomes globally. The Principal Knowledge Graph Engineer will lead the design and development of a scalable knowledge graph infrastructure that focuses on biomedical data, supporting J&J IM Data Science Portfolio's R&D efforts aimed at target identification, drug design, and knowledge synthesis. This role requires a strong background in semantic technologies, ontology, graph-based data modeling, and a deep understanding of the life sciences domain. In this role, the engineer will lead interdisciplinary teams in mapping complex biomedical relationships, manage project timelines and tasks, and foster team collaboration. They will strengthen engagement with collaborators at all levels, including senior management and domain experts, sharing project findings and actively seeking input to guide the mapping process. The engineer will also develop and maintain ontologies representing domain-specific knowledge in healthcare and life sciences for drug discovery, apply graph-based data modeling techniques for efficient organization and integration of data, and coordinate with advanced analytics and machine learning teams to leverage the knowledge graph for insights and innovation in drug discovery and development. Additionally, they will be responsible for developing high-performance graph query services and managing the graph database infrastructure in collaboration with IT and DevOps teams, promoting best practices in knowledge graph development and providing training sessions for key collaborators.

Responsibilities

• Lead the design and development of a scalable knowledge graph infrastructure focusing on biomedical data.
• Support J&J IM Data Science Portfolio's R&D efforts aimed at target ID/Validation, drug design, and knowledge synthesis.
• Lead interdisciplinary teams in mapping complex biomedical relationships.
• Manage project timelines, tasks, and foster team collaboration.
• Drive clear objectives, supervise progress, and address obstacles and risks.
• Strengthen collaborator engagement at all levels, including senior management, domain experts, and decision-makers.
• Share project findings, provide updates, and actively seek input for guiding the mapping process.
• Develop and maintain ontologies representing domain-specific knowledge in healthcare and life sciences for drug discovery.
• Apply graph-based data modeling techniques for efficient organization, integration, and data retrieval.
• Coordinate with advanced analytics and machine learning teams to use knowledge graph for insights, predictions, and innovation in drug discovery and development.
• Collaborate with multi-functional teams to translate business challenges into knowledge-graph-based technical solutions.
• Develop and optimize high-performance graph query services and incorporate complex data retrieval systems for NLP-based data discovery.
• Work with IT and DevOps teams to deploy and manage the graph database infrastructure, focusing on high availability, scalability, and recovery operations.
• Promote standard methodologies in knowledge graph development, offering workshops, and training sessions for key collaborators.
• Create and be responsible for documentation, such as data dictionaries, data lineage, and data flow diagrams, to facilitate understanding of the knowledge graph.

Requirements

• Ph.D. or master's degree in bioengineering, computer science, IT, bioinformatics, physics, mathematics, or related fields, with an emphasis on semantic technologies and biomedical application.
• At least 5 years of professional experience in health informatics, or at least 7 years of professional experience with additional consideration for candidates with graduate degrees or equivalent experience.
• Programming background in parser combinators, natural language processing, and linked data (RDF Triple Stores and property graphs).
• Demonstrated experience in large-scale knowledge graphs construction, ontology development, and integration in pharmaceutical or healthcare domains.
• Proficiency in semantic web technologies (SPARQL, RDF, OWL) and familiarity with graph databases (Neo4j, Amazon Neptune).
• Proven work with complex biomedical datasets, including genomics, proteomics, and high-throughput screening data.
• Experience in various data storage solutions (SQL, key-value, column, document, graph stores) and data modeling techniques (semantic data, ontologies, taxonomies).
• Experience in CI/CD implementations, git usage, CI/CD stacks (Jenkins, GitLab, Azure DevOps), DevOps tools, metrics/monitoring, and containerization technologies (Docker, Singularity).
• Strong skills in analysis, problem-solving, organizational change, project delivery, and managing external vendors.
• Excellent skills in customer focus, networking, communication, and presentation; experience in line and multi-functional management styles.
• Demonstrated agile decision-making, performance management, continuous learning, and commitment to quality.

Nice-to-haves

• Experience in a pharmaceutical, biotech, or related research environment is preferred.
• Capacity to translate discussions into user requirements and project plans.

Benefits

• Expected Base Salary: $135k - $202k
• Flexible work location options including remote work.
• Opportunities for professional development and training.