Senior Data Architect

Job Description Senior Data Architect Summary

Cerebro Technologies is a fast-growing tech startup that has built a world-class computer vision AI platform to modernize manufacturing operations. Our 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 — the core engine that turns computer vision streams into production intelligence. This senior leadership role demands deep technical expertise in designing and operating world-class, large-scale cloud data architectures combined with a forward-looking vision for future-proof, AI-native platforms. You will architect bidirectional streaming pipelines, lead MCP (Model Context Protocol) pipelines and agentic AI capabilities, and guide a high-performing team that already brings strong domain knowledge of manufacturing metrics and insights.

You will leverage AI not only to strengthen internal product pipelines but to deliver direct, measurable value to customers through smarter, proactive, autonomous insights. If you have proven experience building production-grade data platforms at scale (as seen at leading tech companies like Tesla, SpaceX, or NVIDIA) and you’re excited to drive the next generation of agentic AI in a high-impact environment, this is your opportunity to shape the future.

• FGF believes in Home Grown Talent, accelerated career growth with leadership training. Unleashing Your Potential
• Competitive Compensation, Health Benefits, & a generous flexible medical / Health spending account
• RRSP matching program
• Tuition reimbursement
• Discount program that covers almost everything under the sun - Restaurants, gyms, shopping etc.

• Data Architecture & Future-Proof Platform Leadership
• 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,…