Senior Lead, Knowledge Engineer

S&P Global Market Intelligence; Hyderabad; On-site; INR 1,500,000 - 2,100,000; Full time

Job summary

S&P Global Market Intelligence is seeking a Lead Knowledge Engineer to drive ontologies, knowledge graphs and semantic artefacts within the Knowledge Engineering team. You will collaborate with data and software engineering to advance data architecture and tooling, shaping our interconnected data strategy.

The role requires translating complex technical strategies for both technical and non-technical stakeholders, leading strategic projects, and guiding governance to promote semantic standards

Qualifications

• 5+ years of ontology development and semantic web tech.
• 3+ years in advanced data integration with semantic/knowledge graphs in complex environments.
• Programming in Python/Java/JavaScript with cloud services experience.

Responsibilities

• Develop and enhance ontologies, taxonomies, and knowledge graphs.
• Design data/software solutions to scale semantic artefacts.
• Provide leadership for strategic semantic projects and timelines.
• Influence the semantic vision, roadmap, and architecture.
• Create linked metadata schemes to harmonize semantics.
• Analyze and implement knowledge organization strategies with tooling.
• Participate in governance to promote semantic standards.

Skills

Ontology development

Semantic web technologies

RDF / RDFS / OWL / SPARQL

Python / Java / JavaScript

Cloud services (AWS / GCP / Azure)

Stakeholder communication

Education

Advanced degree in CS / Knowledge Engineering

Tools

VocBench

TopQuadrant

PoolParty

RDFLib

Triple stores

Job description

Job Summary

About the Role: Lead Knowledge Engineer

Grade Level (for internal use): 12

The Role: Lead Knowledge Engineer

The Team:

The Knowledge Engineering team within Distribution & Data Platforms 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.

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)