Analytics & AI Data Architect - Operate
Deloitte View all jobs
- Toronto, ON
- $72,000-138,000 per year
- Temporary
- Full-time
Work Model: Hybrid
Reference code: 132793
Primary Location: Toronto, ON
All Available Locations: Toronto, ONOur PurposeAt Deloitte, our Purpose is to make an impact that matters. We exist to inspire and help our people, organizations, communities, and countries to thrive by building a better future. Our work underpins a prosperous society where people can find meaning and opportunity. It builds consumer and business confidence, empowers organizations to find imaginative ways of deploying capital, enables fair, trusted, and functioning social and economic institutions, and allows our friends, families, and communities to enjoy the quality of life that comes with a sustainable future. And as the largest 100% Canadian-owned and operated professional services firm in our country, we are proud to work alongside our clients to make a positive impact for all Canadians.By living our Purpose, we will make an impact that matters.
- Have many careers in one Firm.
- Enjoy flexible, proactive, and practical benefits that foster a culture of well-being and connectedness.
- Learn from deep subject matter experts through mentoring and on the job coaching
- Proven experience in data analysis and data architecture, supporting analytics and AI‑driven use cases.
- Strong hands‑on experience creating and maintaining data dictionaries, including clear definitions, ownership, and data lineage.
- Demonstrated expertise in data modeling (logical and physical) to support analytics, AI, and reporting solutions.
- Experience with attribute‑to‑document and attribute‑to‑source mapping, enabling traceability, explainability, and audit readiness.
- Working knowledge of vector databases and their application in AI use cases such as semantic search and retrieval‑augmented generation (RAG).
- Strong understanding of data quality principles, with experience defining, implementing, and monitoring data quality rules.
- Ability to collaborate effectively with data scientists, engineers, and business stakeholders to translate requirements into scalable data solutions.
- Experience supporting analytics, AI, or machine‑learning initiatives is considered an asset.