Data Architect

Project Role : Data Architect Project Role Description : Define the data requirements and structure for the application. Model and design the application data structure, storage and integration. Must have skills : Microsoft Azure Data Services Good to have skills : Graph Databases, Data Engineering Minimum 7.5 year(s) of experience is required Educational Qualification : 15 years full time education Summary: AI Powered Tech Talent Role Summary / Description Senior Engineer role in Knowledge Engineering focused on designing, building, and leading significant workstreams for enterprise-scale Knowledge Graph, semantic layer, ontology, and AI knowledge solutions on Microsoft Azure. In this role, the successful candidate leads a substantial knowledge engineering scope within a large program, translates real-world business problems into scalable AI and KG solutions, guides technical direction, and contributes to thought leadership, reusable assets, and delivery standards. The role must bring relevant industry experience across domains such as BFSI, healthcare, retail, telecom, manufacturing, energy, public sector, or life sciences, applying semantic AI, knowledge graphs, LLM grounding, data pipelines, and cloud-native engineering patterns to deliver measurable client value.

Engineer Azure-based knowledge engineering solutions using services such as Azure Data Lake Storage, Azure Data Factory, Azure Synapse/Fabric, Azure AI Search, Azure OpenAI, Azure Machine Learning, AKS, Microsoft Purview, Entra ID, APIs, and Azure Monitor. Build graph ingestion pipelines, semantic data products, vector integrations, LLM grounding layers, APIs, and governed access patterns on Azure while improving performance, reliability, scalability, and cost efficiency. Lead the build of Knowledge Graph solutions that transform client data architecture within a large program scope. Direct the design, development, and implementation of AI, semantic layer, ontology, taxonomy, schema, graph modeling, and knowledge curation solutions, ensuring all components work together seamlessly. Work with project leaders, delivery leads, client stakeholders, architects, data engineers, AI engineers, product teams, and domain SMEs to create standout graph-powered data and AI offerings. Develop strong client relationships, earn trust as a key advisor, and explain the business value of semantic layer, ontology, and knowledge graph solutions. Make the business case for the recommended semantic layer solution and contribute meaningfully to sales, pre-sales, estimation, proposal inputs, and solution shaping activities. Provide thought leadership on technology trends, innovation opportunities, limitations, risks, delivery concerns, and practical adoption of knowledge graphs, semantic AI, LLM grounding, RAG, and agentic systems. Design, evaluate, and maintain ontologies, schemas, standards, and reusable engineering patterns, while guiding teams on data model quality and implementation methods. Lead a team or workstream within a larger program, mentor engineers, review design/code/configuration, and guide adoption of new methodologies, model building techniques, and algorithms. Collaborate across business and technical teams to drive end-to-end delivery for the assigned scope and demonstrate value to business and technology stakeholders.

Bachelor's degree or equivalent in Computer Science, Information Technology, Engineering, Mathematics, Data Science, or a related field. Minimum 3 years of experience with Knowledge Graph technologies such as RDF, SPARQL, LPG, SHACL, OWL, graph query languages, schema design, ontology management, and KG curation. Minimum 3 years of experience in schema design, ontology management, semantic modeling, taxonomy management, metadata management, and knowledge graph curation. Minimum 3 years of experience designing and developing Knowledge Graph solutions and graph-based ML models across functional and technical