Job Description Join RBC's Cloud Data Lake Platform (Snowflake) Engineering team as a Staff Data Platform Engineer, where you will design, build, and operate one of Canada's largest enterprise data platforms. The 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.What is the opportunity? Work on the in‑house Snowflake Control Plane – a Python‑based platform that automates provisioning, enforces RBAC, manages disaster recovery, and governs interactions with Snowflake. Focus on enabling Snowflake’s AI capabilities (Cortex AI) in a secure, governed, and compliant manner. The team is flat, collaborative, and values mentorship and continuous learning.What will you do? Platform Engineering & AI EnablementDesign, develop, and maintain the Snowflake Control PlaneEnable new Snowflake features with appropriate governance controls, access policies, and compliance guardrailsCollaborate with Model Risk and Compliance teams on AI governance frameworks and responsible AI adoptionSecurity & ComplianceImplement and maintain security controls – OAuth/SSO integrations, JWT validation, secret management with HashiCorp Vault and Azure Key Vault, and credential lifecycle automationEnforce platform security posture including rate limiting, input sanitization, and security headersDrive compliance with enterprise security standards and OSFI guidelines, particularly for AI/ML workloadsDeveloper Experience & OperationsBuild self‑service workflows and automation for user onboarding, resource provisioning, and platform managementOperate and improve CI/CD pipelines with progressive deployment, security scanning (SAST, SCA, DAST), and code quality gatesCreate technical documentation and contribute to platform observability and monitoringTechnical LeadershipLead architectural decisions and present trade‑offs to technical leadershipMentor junior engineers and co‑op students on platform engineering and security best practicesParticipate actively in agile ceremonies, PI planning, and sprint demosWhat do you need to succeed? Must‑Have Technical SkillsPython (Expert): Deep proficiency in Python 3.11+, FastAPI, Pydantic v2, async/await patterns, and building production‑grade APIsSnowflake: 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, and multi‑cloud service deliverySecurity Engineering: Deep understanding of OAuth 2.0 / OIDC, JWT validation, RBAC design, secret management, and enterprise security patterns; experience implementing security controls in production systemsAI/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 deploymentsCI/CD & DevOps: Experience with GitHub Actions (or similar), container‑based deployments (Docker, OpenShift/Kubernetes), progressive delivery strategies, and security scanning (SAST, SCA, DAST)Core CompetenciesSystems Thinking – reason about distributed systems, connection pooling, failover strategies, and end‑to‑end implications of enabling AI features on an enterprise data platformSecurity Mindset – instinctive focus on least‑privilege access, defense‑in‑depth, audit trails, and complianceTechnical Leadership – proven ability to drive architectural decisions, influence without authority, and articulate technical strategy to both engineering peers and business stakeholdersCommunication – excellent written and verbal skills; presenting to internal key decision‑making teams, writing governance documentation, and mentoring engineersOwnership & Accountability – self‑driven with a track record of delivering complex, cross‑cutting initiatives from design through productionEducation & ExperienceBachelor's degree in Computer Science, Engineering, or equivalent practical experience7+ years of experience in platform engineering, data engineering, cloud engineering, or SRE roles3+ years working with Snowflake or comparable enterprise data platforms at scaleExperience operating in regulated environments (financial services, healthcare, or government)Nice‑to‑HaveSnowflake Cortex AI – hands‑on experience with Cortex Analyst, Cortex Search, Cortex AgentsSnowPro Certifications – SnowPro Core, Advanced: Architect, or Advanced: Data EngineerTemporal / Workflow Orchestration – experience with Temporal, Airflow, Step Functions, or similar durable workflow enginesObservability – hands‑on with Dynatrace, Datadog, Prometheus/Grafana, or ELK Stack for APM and platform monitoringInfrastructure as Code – Terraform, CloudFormation, or similar, for cloud resource managementAPI 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 frameworksLLM/GenAI Security – knowledge of prompt injection risks, data leakage prevention, and AI‑specific threat modelsWhat's in it for you?Become part of a team that works collaboratively; mentors and coaching for personal developmentA comprehensive Total Rewards Program including bonuses, flexible benefits, competitive compensation, commissions, and stock options where applicableLeaders who support your development through coaching and managing opportunitiesAbility to make a difference and lasting impact from a local‑to‑global scaleInclusion and Equal Opportunity Employment RBC is an equal opportunity employer committed to diversity and inclusion. All qualified applicants are considered without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, protected veterans status, Aboriginal/Native American status, or any other legally‑protected factor. Disability‑related accommodations during the application process are available upon request.Location RBC WATERPARK PLACE, 88 QUEENS QUAY Waterpark TorontoJob DetailsWork hours/week: 37.5Employment Type: Full timePlatform: TECHNOLOGY AND OPERATIONSJob Type: RegularPay Type: SalariedPosted Date: 2026‑05‑05Application Deadline: 2026‑05‑31Where to learn more Visit jobs.rbc.com to stay informed about great career opportunities at RBC.#J-18808-Ljbffr