Senior Data Architect

fgf brands • Toronto, ON

10d

About The Position

Cerebro Technologies is a fast-growing tech startup that has built a world-class computer vision AI platform to modernize manufacturing operations. Their proprietary AI software, powered entirely by cameras, has been successfully deployed across 30+ factories and 120+ manufacturing lines worldwide. As Senior Data Architect, you will own and evolve the entire Data Analytics platform, which is the core engine that transforms computer vision streams into production intelligence. This senior leadership role requires deep technical expertise in designing and operating world-class, large-scale cloud data architectures, coupled with a forward-looking vision for future-proof, AI-native platforms. You will be responsible for architecting bidirectional streaming pipelines, leading MCP (Model Context Protocol) pipelines and agentic AI capabilities, and guiding a high-performing team that possesses strong domain knowledge of manufacturing metrics and insights. The role involves leveraging AI to strengthen internal product pipelines and deliver direct, measurable value to customers through smarter, proactive, autonomous insights. This is an opportunity to shape the future for individuals with proven experience in building production-grade data platforms at scale and a passion for driving the next generation of agentic AI in a high-impact environment.

Requirements

• 10+ years of progressive experience in data architecture or data engineering, with at least 4+ years in a lead or principal role designing and operating enterprise-scale cloud data platforms.
• Proven hands-on experience building and running world-class, large-scale, production-grade data architectures (Databricks Lakehouse + MongoDB or equivalent modern stacks).
• Deep expertise with Databricks (Delta Lake, Structured Streaming, Auto Loader, Unity Catalog, PySpark / Spark SQL) and MongoDB Atlas (document modeling, aggregation framework, change streams, indexes, Atlas triggers).
• Demonstrated success designing and operating bidirectional or multi-directional streaming pipelines at scale.
• Strong practical experience building, deploying, and supporting MCP (Model Context Protocol) pipelines and agentic AI systems — enabling AI agents to reason over governed data and deliver proactive value.
• Genuine passion and proven ability to leverage AI to build better product pipelines and deliver direct added value to customers.
• Forward-looking technical vision with a track record of designing future-proof, AI-native architectures that scale effortlessly and incorporate emerging capabilities.
• Strong command of Python, advanced SQL, and data modeling across analytical and operational paradigms.
• Excellent communication and leadership skills — able to translate complex technical and AI concepts for both technical teams and non-technical stakeholders.

Responsibilities

• Lead the design, evolution, and governance of our enterprise data platform spanning Databricks Lakehouse (Delta Lake) and MongoDB Atlas, ensuring it is highly scalable, reliable, cost-efficient, and engineered for long-term growth at global scale.
• Define and evolve data models, schemas, and taxonomies that support both analytical and operational workloads.
• Set architectural standards and a visionary roadmap that anticipates future scale, emerging AI capabilities, and evolving data demands — keeping the platform ahead of industry standards.
• Continuously evaluate and introduce new technologies and patterns to maintain a truly future-proof, AI-native architecture.
• Architect and implement high-performance, real-time bidirectional pipelines (Databricks, MongoDB) using Databricks Structured Streaming, Auto Loader, Delta Live Tables, Unity Catalog, and the MongoDB Spark Connector.
• Design, build, deploy, and support MCP (Model Context Protocol) pipelines that securely expose governed data, models, and metadata to AI agents.
• Develop and operationalize agentic AI systems that enable intelligent agents to reason over data, trigger actions, and generate proactive, context-rich insights for end users.
• Leverage agentic AI and MCP to enhance both internal product pipelines and customer-facing capabilities — turning data into autonomous insights and actionable intelligence that deliver measurable customer value.
• Partner with the Data Science and Mobile teams to embed AI agents into operator workflows and decision-making processes.
• Design the MongoDB data layer that powers shop-floor applications, dashboards, and reporting, with native support for agentic interactions via MCP.
• Define clear data contracts and versioned interfaces between the data platform and application layers.
• Implement enterprise-grade data cataloging, lineage, metadata management, quality rules, and schema evolution — with specific focus on governance required for safe, scalable agentic AI deployment.
• Lead and mentor the Data Analytics team (who already possess strong knowledge of manufacturing metrics and insights) — own hiring, technical direction, coaching, and career development.
• Collaborate closely with Data Science, Mobile, and Customer Success teams to translate business needs into robust, AI-powered data solutions.
• Produce clear architecture documentation, roadmaps, and diagrams that communicate both technical depth and strategic vision.

Benefits

• Competitive Compensation
• Health Benefits
• generous flexible medical / Health spending account
• RRSP matching program
• Tuition reimbursement
• Discount program that covers almost everything under the sun - Restaurants, gyms, shopping etc.
• accelerated career growth with leadership training

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed
• Number of Employees: 501-1,000 employees