Job Description

About the Role: Grade Level (for internal use): 11 The Role : The Knowledge Engineering team are seeking a Lead Knowledge Engineer to support our strategic transformation from a traditional data organization into a next generation interconnected data intelligence organization. The Team : The Knowledge Engineering team within data strategy and governance helps to lead fundamental organizational and operational change driving our linked data, open data, and data governance strategy, both internally and externally. The team partners closely with data and software engineering to envision and build the next generation of data architecture and tooling with modern technologies. The Impact : Knowledge Engineering efforts occur within the broader context of major strategic initiatives to extend market leadership and build next-generation data, insights and analytics products that are powered by our world class datasets. Whats in it for you : The Lead Knowledge Engineer role is an opportunity to work as an individual contributor in creatively solving complex challenges alongside visionary leadership and colleagues. Its a role with highly visible initiatives and outsized impact. The wider division has a great culture of innovation, collaboration, and flexibility with a focus on delivery. Every person is respected and encouraged to be their authentic self. Responsibilities : Develop, implement, and continue to enhance ontologies, taxonomies, knowledge graphs, and related semantic artefacts for interconnected data, as well as topical/indexed query, search, and asset discovery Design and prototype data / software engineering solutions enabling to scale the construction, maintenance and consumption of semantic artefacts and interconnected data layer for various application contexts Provide thought leadership for strategic projects ensuring timelines are feasible, work is effectively prioritized, and deliverables met Influence the strategic semantic vision, roadmap, and next-generation architecture Execute on the interconnected data vision by creating linked metadata schemes to harmonize semantics across systems and domains Analyze and implement knowledge organization strategies using tools capable of metadata management, ontology management, and semantic enrichment Influence and participate in governance bodies to advocate for the use of established semantics and knowledge-based tools Qualifications: Able to communicate complex technical strategies and concepts in a relatable way to both technical and non-technical stakeholders and executives to effectively persuade and influence 5+ years of experience with ontology development, semantic web technologies (RDF, RDFS, OWL, SPARQL) and open-source or commercial semantic tools (e.g., VocBench, TopQuadrant, PoolParty, RDFLib, triple stores); Advanced studies in computer science, knowledge engineering, information sciences, or related discipline preferred 3+ years of experience in advanced data integration with semantic and knowledge graph technologies in complex, enterprise-class, multi-system environment(s); skilled in all phases from conceptualization to optimization Programming skills in a mainstream programming language (Python, Java, JavaScript), with experience in utilizing cloud services (AWS, Google Cloud, Azure) is a great bonus Understanding of the agile development life cycle and the broader data management discipline (data governance, data quality, metadata management, reference and master data management) S&P Global Enterprise Data Organization is a unified, cross-divisional team focused on transforming S&P Globals data assets. We streamline processes and enhance collaboration by integrating diverse datasets with advanced technologies, ensuring efficient data governance and management.