Who you'll be:

The Data Architect (SME) is responsible for leading the design and management of the organization’s enterprise data environment, ensuring information is accurate, connected, and supports advanced analytics and AI. This role integrates traditional databases with modern data platforms and semantic/knowledge-graph technologies to provide meaningful insights and smarter decision-making. The SME establishes data standards, ensures secure data sharing, and collaborates with engineering and AI teams to maintain structured, governed, and high-quality data.

What you'll do:

• Design and maintain enterprise data architectures that integrate multiple data systems.
• Build and manage knowledge graphs, ontologies, and metadata structures to improve data context and discovery.
• Develop secure, well-governed data pipelines and processes for high-quality, trusted data.
• Support AI and analytics teams by providing structured, contextual data for model development and retrieval workflows.
• Establish data governance, data quality, and metadata standards across the organization.
• Evaluate new technologies and recommend improvements to data platforms and processes.
• Ensure data sharing and access follow security, compliance, and zero trust requirements.

What you need:

• Bachelor's degree required.
• Minimum of 10 years of experience in data architecture, data engineering, or related areas.
• Strong experience with enterprise data platforms, distributed systems, and modern data pipelines.
• Familiarity with semantic technologies (RDF, OWL, SPARQL), ontologies, and knowledge graph design.
• Experience with metadata management, data lineage, and data governance processes.
• Knowledge of cloud data services and secure, multi-environment data integrations.
• Ability to communicate complex technical concepts clearly to non-technical stakeholders.

Unique Skills / Technical Requirements:

• In-house custom developed application.
• Advanced AI, GenAI & Multi-Model Engineering, including multi-model and multi-modality orchestration.
• Provenance and end-to-end data lineage tracking.
• Air gapped, hybrid, and on-premise operational environments.
• UI, backend, and middleware engineering using TypeScript, React, Python, and other modern technologies.

Nice to have:

• Experience supporting AI/ML teams, retrieval architectures, or vector-based search.
• Background working in secure, multi-enclave, or zero trust environments.
• Experience with streaming data, real-time processing, or hybrid cloud architectures.
• Advanced degree in Computer Science, Information Science, Data Engineering, or related field.