Senior Azure Data Architect leading the architecture, design, and delivery of data models, products, and solutions for global mining operations.

Our mining client is looking for a Senior Azure Data Architect leading the architecture, design, and delivery of data models, products, and solutions for global mining operations.

Vancouver, Permanent, on-sight (5 days a week), $150k to $170k per annum (with 20% bonus and no equity involved), travel 1 or 2 weeks annual to Chile or US

Must Have:

• 8+ years experience as a Data Architect, with Azure Analytics stack (Azure Data Factory, Azure Data Lake)
• Preferred experience within mining, process manufacturing, industrial manufacturing, or resource industries (oil and gas, chemicals)
• Exposure to standard DevOps processes supporting data platforms.
• Expertise in data modeling and designing data platforms for large-scale data and diverse architectures (e.g., warehouses, lakehouses)
• Strong knowledge of SQL, database design concepts, and Master Data Management (MDM) principles.

Nice to Have:

• Proficiency in English, Spanish, Portuguese (important for work with South American sites)
• Post-secondary degree in Computer Science, Software Engineering, or related fields in Data Engineering, Data Analysis, AI, or ML.
• Familiarity with analytics techniques using Machine Learning (ML) and Artificial Intelligence (AI).
• Experience designing and implementing event-driven or streaming data solutions.
• Understanding of data security, privacy, and compliance with global regulations (e.g., GDPR, PIPEDA).
• Exposure to standard DevOps processes supporting data platforms.

Responsibilities:

• Role is more “hands-off” and does not involve day-to-day data engineering (outsourced), focus on strategy, architecture, and maintaining the Azure Data Lake instance
• Lead architecture, design, and delivery of data models, products, and solutions for global mining operations.
• Provide design oversight and guidance to site-level data teams on pipeline development, model development, and analytics.
• Establish guidelines, controls, and processes for scalable data-driven solutions.
• Design and implement curated data models for unified analytics and reporting.
• Lead technology proof of concepts to evaluate new data technology solutions.