Data Architect in Toronto

Tiger Analytics is an advanced analytics consulting firm. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our consultants bring deep expertise in Data Science, Machine Learning, and AI.

We are looking for a Data Architect, who will directly engage with cross-functional business, AI, and engineering teams to design and deploy scalable, production-grade Knowledge Graph solutions and robust Data Governance frameworks. This role will bridge complex semantic data modeling with real-world enterprise applications to drive contextual AI and unified metadata management.

Responsibilities

• Knowledge Graph Engineering: Architect, design, and deploy enterprise Knowledge Graph solutions using Property Graphs and semantic technologies.
• Semantic Modeling: Build, maintain, and extend ontologies, taxonomies, metadata models, and enterprise knowledge structures tailored to client domain requirements.
• Data Governance & Metadata Management: Establish integrated data governance frameworks, including end-to-end data lineage, automated metadata management, business glossaries, data stewardship workflows, and data quality standards.
• Cross-Functional Collaboration: Partner closely with business stakeholders, AI/ML engineers, and data platforms teams to translate complex business domains into scalable semantic models.
• Technical Integration: Integrate knowledge graphs into broader enterprise data fabrics, data meshes, and AI systems (e.g., Graph-RAG, LLM context engines).
• Delivery & Leadership: Act as a technical authority on customer deployments, translating ambiguous client needs into clean, scalable data architecture blueprints.

Qualifications

• Knowledge Graphs: Proven experience designing and delivering enterprise Knowledge Graph systems in production.
• Semantic Foundations: Deep expertise in ontology modeling, taxonomy development, metadata architectures, and Property Graph models (e.g., Neo4j, Amazon Neptune, Cosmos DB).
• Governance Expertise: Strong track record in enterprise Data Architecture and Governance, including hands-on experience with metadata lineage, data quality platforms, stewardship frameworks, and enterprise business glossaries.
• Cross-Domain Execution: Demonstrated ability to bridge technical AI/engineering teams and non-technical business stakeholders to drive consensus on data models.
• Technical Stack: Proficiency with graph query languages (Cypher, Gremlin, or SPARQL), graph databases, and modern data stack integration pattern (ETL/ELT pipelines, APIs, and cloud platforms).

Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.

Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.