Job DescriptionWhat is the opportunity?Join RBC's
Cloud Data Lake Platform (Snowflake) Engineering team as a
Staff Data Platform Engineer, where you'll play a critical role in designing, building, and operating one of Canada's largest enterprise data platforms. Our team empowers thousands of Data Scientists, Analysts, and business users across RBC with self-serve analytics capabilities built on Snowflake, delivered through a multi-cloud architecture spanning AWS and Azure.
You'll work on our in-house Snowflake Control Plane - a Python-based platform that automates provisioning, enforces RBAC, manages disaster recovery, and governs how the enterprise interacts with Snowflake. A key focus of this role is enabling
Snowflake's AI capabilities (Cortex AI) in a
secure, governed, and compliant manner.
What will you do?Platform Engineering & AI Enablement- Design, develop, and maintain the Snowflake Control Plane
- Enable Snowflake new features with appropriate governance controls, access policies, and compliance guardrails
- Collaborate with Model Risk and Compliance teams on AI governance frameworks and responsible AI adoption
Security & Compliance- Implement and maintain security controls - OAuth/SSO integrations, JWT validation, secret management (HashiCorp Vault, Azure Key Vault), and credential lifecycle automation
- Enforce platform security posture including rate limiting, input sanitization, and security headers
- Drive compliance with enterprise security standards and OSFI guidelines, particularly for AI/ML workloads
Developer Experience & Operations- Build self-service workflows and automation for user onboarding, resource provisioning, and platform management
- Operate and improve CI/CD pipelines with progressive deployment, security scanning (SAST, SCA, DAST), and code quality gates
- Create technical documentation and contribute to platform observability and monitoring
Technical Leadership- Lead architectural decisions and present trade-offs to technical leadership
- Mentor junior engineers and co-op students on platform engineering and security best practices
- Participate actively in agile ceremonies, PI planning, and sprint demos
What do you need to succeed?Must-HaveTechnical Skills- Python (Expert): Deep proficiency in Python 3.11+, FastAPI, Pydantic v2, async/await patterns, and building production-grade APIs
- Snowflake: Strong working knowledge of Snowflake architecture - roles, databases, schemas, warehouses, stages, storage integrations, failover groups, replication, and AI Suite. Experience with Snowflake security (OAuth, key pair auth, network policies)
- Cloud Platforms: Hands-on experience with AWS and Azure - IAM, networking, storage, secret management (Vault, AKV), and multi-cloud service delivery
- Security Engineering: Deep understanding of OAuth 2.0 / OIDC, JWT validation, RBAC design, secret management, and enterprise security patterns. Experience implementing security controls in production systems
- AI/ML Governance: Understanding of responsible AI principles, model risk management, AI auditing requirements, and regulatory frameworks (OSFI, NIST AI RMF) as they apply to enterprise AI deployments
- CI/CD & DevOps: Experience with GitHub Actions (or similar), container-based deployments (Docker, OpenShift/Kubernetes), progressive delivery strategies, and security scanning (SAST, SCA, DAST)
Core Competencies- Systems Thinking: Ability to reason about distributed systems, connection pooling, failover strategies, and the end-to-end implications of enabling AI features on an enterprise data platform
- Security Mindset: Instinctive focus on least-privilege access, defense-in-depth, audit trails, and compliance
- Technical Leadership: Proven ability to drive architectural decisions, influence without authority, and articulate technical strategy to both engineering peers and business stakeholders
- Communication: Excellent written and verbal skills - you'll be presenting to various internal key decision-making teams, writing governance documentation, and mentoring engineers
- Ownership & Accountability: Self-driven with a track record of delivering complex, cross-cutting initiatives from design through production
Education & Experience- Bachelor's degree in Computer Science, Engineering, or equivalent practical experience
- 7+ years of experience in platform engineering, data engineering, cloud engineering, or SRE roles
- 3+ years working with Snowflake or comparable enterprise data platforms at scale
- Experience operating in regulated environments (financial services, healthcare, or government)
Nice-to-Have- Snowflake Cortex AI: Hands-on experience with Cortex Analyst, Cortex Search, Cortex Agents
- SnowPro Certifications: SnowPro Core, Advanced: Architect, or Advanced: Data Engineer
- Temporal / Workflow Orchestration: Experience with Temporal, Airflow, Step Functions, or similar durable workflow engines
- Observability: Hands-on with Dynatrace, Datadog, Prometheus/Grafana, or ELK Stack for APM and platform monitoring
- Infrastructure as Code: Terraform, CloudFormation, or similar, for cloud resource management
- API Design: Experience designing and evolving large API surfaces (RESTful, OpenAPI/Swagger)
- Financial Services: Understanding of Canadian regulatory landscape (OSFI B-13, PIPEDA) and enterprise risk frameworks
- LLM/GenAI Security: Knowledge of prompt injection risks, data leakage prevention, and AI-specific threat models
What's in it for you?- Become part of a team that thinks progressively and works collaboratively. We care about seeing each other reach full potential;
- A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock options where applicable;
- Leaders who support your development through coaching and managing opportunities;
- Ability to make a difference and lasting impact from a local-to-global scale.
About RBC BorealisRBC Borealis is the driving force behind Royal Bank of Canada's AI and data innovation. As part of Canada's largest financial institution, we bring together a team of architects, engineers, scientists, and product experts on a mission to revolutionize finance through world-class research, solutions, and a resilient data platform. With locations across Toronto, Waterloo, Montreal, Calgary, and Vancouver, we're at the forefront of AI research and platform development. With a focus on cutting-edge research in areas like time series forecasting, causal machine learning, and responsible AI, we are seamlessly integrating AI research and data engineering, to solve critical challenges in the financial industry. We are building intelligent, and scalable, data-driven solutions that will help communities thrive and drive innovation for our customers across the bank.
Job SkillsActive Learning, Agile Methodology, Application Integrations, Detail-Oriented, Enterprise Application Delivery, Group Problem Solving, Programming Languages, Software Development Life Cycle (SDLC)
Additional Job DetailsAddress:RBC WATERPARK PLACE, 88 QUEENS QUAY W:TORONTO
City:Toronto
Country:Canada
Work hours/week:37.5
Employment Type:Full time
Platform:TECHNOLOGY AND OPERATIONS
Job Type:Regular
Pay Type:Salaried
Posted Date:2026-05-05
Application Deadline:2026-07-31
Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above
RBC is presently inviting candidates to apply for this existing vacancy. Applying to this posting allows you to express your interest in this current career opportunity at RBC. Qualified applicants may be contacted to review their resume in more detail.
