Head of Platform
Datatonic · Full-time · Posted 3w ago
Shape the Future of Data & AI with Us
At Datatonic, we are Google Cloud's premier partner in AI, driving transformation for world-class businesses. We push the boundaries of technology with expertise in machine learning, data engineering, and analytics on Google Cloud. By partnering with us, clients future-proof their operations, unlock actionable insights, and stay ahead of the curve in a rapidly evolving world.
As Head of Platforms for AMER, you will own the design and delivery of enterprise-scale Google Cloud platforms for our clients. At Datatonic, "platform" means the full stack that use cases run on: cloud landing zones, enterprise data platforms, MLOps platforms and integrated Data & AI platforms. You'll lead the practice and stay close to the build.
Your core belief is that every platform we build should improve on the last, and every use case should be faster, safer and cheaper to deliver than the one before. You'll spot the patterns that recur across client engagements and turn them into internal assets (reusable templates and best practices) that let teams go from idea to production in weeks, not months. You'll pair this with an appreciation for strong enablement that allows client and Datatonic teams to rapidly become self-sufficient on the platforms we build.
You'll design platforms built for scale: capable of deploying and operating many data products and AI agents, serving many kinds of consumers: people using BI and reporting tools, applications calling APIs, and AI agents consuming data through MCP and other interfaces. You'll use agents to run platforms more efficiently, and you'll make the value of the platform visible by combining FinOps with capabilities that measure the business impact of every use case deployed on it.
What You’ll Do
Platform strategy & architecture: Own the reference architectures for Google Cloud landing zones, data platforms (e.g. BigQuery, Knowledge Catalog, Looker), MLOps (Gemini Enterprise Agent Platform) and Data & AI platforms, ensuring they are secure, governed, scalable and aligned to client business goals.
Templates & accelerators: Build and evolve a library of reusable platform templates (infrastructure-as-code modules, CI/CD pipelines, data product and agent blueprints) and drive their adoption so every new use case starts from a proven, production-ready baseline.
Best practices & enablement: Define the standards, patterns and guardrails for how use cases are built on the platform, and lead enablement (playbooks, training, developer experience) so client teams can build confidently and independently.
Scaling use cases: Put in place the capabilities needed to deploy data products and AI agents at scale: automated deployment, environment management, data contracts, evaluation and testing, observability, security, and governance across the use case lifecycle.
Multi-consumption layers: Design consumption layers that serve both people and machines: semantic layers and BI/reporting tools, APIs, and MCP servers that expose governed data and tools to AI agents.
Agentic platform operations: Design, build and deploy agents that help run the platform (e.g. incident triage, cost anomaly detection, access requests, policy and configuration drift, and routine operational tasks), improving reliability while reducing operational overhead.
FinOps & value measurement: Embed FinOps practices (cost allocation, forecasting, unit economics, optimisation) and build the telemetry and reporting that connect platform cost to the business value delivered by each use case, so clients can see and prove ROI.
End-to-end ownership: you will be the ultimate business owner for platforms in AMER. You will lead client conversations, scope builds, presentations, etc. being responsible for delivering strong business outcomes and platform-related revenue
Technical Expertise:
Google Cloud & Platform Foundations: Deep, hands-on expertise designing and delivering Google Cloud landing zones, enterprise data platforms, MLOps and Data & AI platforms in production.
Platform-as-a-product thinking: A track record of building reusable templates, blueprints and golden paths, and evidence that they measurably accelerated use case delivery.
Scaling data products & AI agents: Experience taking multiple data products and/or AI agents from prototype to production at scale, including deployment automation, evaluation, monitoring and governance.
Modern consumption architectures: Understanding of semantic layers, BI tooling, APIs and agent-facing interfaces such as the Model Context Protocol (MCP), and how to design data platforms where agents, not just people, are first-class consumers.
Agents for operations: Practical experience, or a strong point of view, on building or deploying agents (e.g. with Vertex AI / Agent Development Kit) to automate and optimise platform operations.
FinOps & value: Experience implementing FinOps frameworks and observability/telemetry that tie cloud spend to business outcomes and use case ROI.
Enterprise fundamentals: Strong grounding in cloud security, identity, networking, infrastructure-as-code (e.g. Terraform), CI/CD and production operations.
Soft Skills & Mindset:
Builder-leader: You've led teams while staying hands-on enough to shape designs and unblock delivery.
Stakeholder Leadership: Strong presentation capabilities with a demonstrated history of advising senior client stakeholders.
Adaptability & Ownership: Ability to navigate ambiguity, manage competing priorities under tight timelines (e.g., 4-week design sprints), and take absolute ownership of project outcomes.
Hands-on experience within Google Cloud (GCP) environments.
Background working within high-growth startups, scale-ups, or modern enterprise transformation environments.
Google Cloud Professional certifications (e.g. Cloud Architect, Data Engineer, Machine Learning Engineer).
End-to-End Impact: Drive the full lifecycle of cutting-edge platforms - from pre-sales and strategy to active deployment in production.
Engineering-First Culture: Work within an architecture group embedded alongside senior and principal engineers, focusing on real execution rather than static slide decks.
Next-Gen AI Exposure: Lead the industry in designing scalable AI agents, evaluation systems, and production guardrails.
Direct Stakeholder Influence: Shape customer transformation strategies by directly connecting technical architecture to business value.
We believe in empowering our team to thrive, with benefits including:
20 days of paid vacation per calendar year
Public Holidays for your Province of Residence
5 Wellness days (sickness, personal time, mental health)
5 Lifestyle days (religious events, volunteer day, sick day)
Matching Group Retirement Savings Plan after 3 months
Competitive Group Insurance plan on Day 1 - individual premium paid 100%!
Virtual Medicine and Family Assistance Program - 100% employer-paid!
Home office budget - We are 100% remote!
CAD $70/month for internet/phone expenses
CAD $1,500 every 3 years for tech accessories and office equipment (monitor, keyboard, mouse, desk, etc.) starting on Day 1
Company-supplied MacBook Pro or Air
CAD $400/year for books, relevant app subscriptions or an e-reader.
Opportunities for paid certifications
Regular company off-sites and meetups
Datatonic is a UK-based company with an Americas division located in Canada. The Canadian team operates remotely, with members distributed across North and South America. This role is open to candidates located anywhere in Canada.
Join us to work alongside AI enthusiasts and data experts who are shaping tomorrow. At Datatonic, innovation isn’t just encouraged - it’s embedded in everything we do. If you’re ready to inspire change and deliver value at the forefront of data and AI, we’d love to hear from you!
Are you ready to make an impact?
Apply now and take your career to the next level.
New Zealand