CAN_Functional Manager
Varite View all jobs
- Toronto, ON
- Permanent
- Full-time
Roles and responsibilities
Program Delivery Leadership Own end-to-end delivery of data platform and AIML operational initiatives discovery design implementation hyper care steady-state operations.
Maintain multi-quarter roadmap| backlog| and release trains (ScrumKanban SAFe) run standups| PI planning| demos| and retros.
Manage dependencies across data ingestion| storage processing| cataloging| lineage| access| MLOps pipelines| and app integrations.
Orchestrate cross-functional squads Data Engineering| Platform SRE| Security| Risk| Legal| and Business to deliver secure| governed| and compliant data capabilities and AI services at scale Own roadmaps| delivery governance| risk controls| release management| and post-production reliability for data AI workloads| ensuring Responsible AI principles are codified into day2 operations.
Platform Technical Ownership Partner with Platform Engineering SRE to evolve the data platform reference architecture Drive integration and operationalization of MLOpsModelOps practices Oversee environment strategy (devteststageprod)| IaC-driven provisioning| cost guardrails| and performance SLAs.
Responsible AI Data Governance Embed Responsible AI guardrails into SDLC and runtime model cards| fairness bias checks| explain ability| human-in-the-loop| monitoring drift| incident response.
Operationalize data governance meta data catalog| lineage| PII classification| DLP| RBACABAC| data quality SLAs| retention deletion schedules.
Align with privacy| security| and regulatory frameworks (e.g.| privacy laws| model risk management| AI assurance frameworks).
Risk| Compliance Controls Maintain risk register| control library| audit trail| approvals| and evidence for releases and model lifecycle events.
Run change advisory (CAB) workflows for platform and model changes ensure traceability from requirements to deployment and monitoring.
Stakeholder Management Communication Translate business outcomes into measurable platform and AI service capabilities and SLIs SLOs.
Provide executive-level status (OKRs| KPIs| burn-up down| RAID| budget vs. actuals)Skills required:
10–12 years in technical program/project management with at least 3–5 years in data platforms and ML/AI operations.
Strong understanding of data architectures (lake/lake house, warehouse, streaming), data governance, and MLOps/ModelOps concepts.
Hands-on familiarity with at least 3 of the following:
Cloud & Data: Azure (Synapse, Fabric), AWS (S3/Glue/Redshift), GCP (BigQuery/Dataflow), Databricks, Snowflake.
MLOps/RAI: Azure ML, SageMaker, Vertex AI; MLflow, model registry, feature stores, drift/fairness/explain ability tools.
Data Governance: Purview, Collibra, Alation; data lineage, cataloging, DQ tooling
Orchestration/CI-CD: Airflow, Prefect, dbt; GitHub Actions/Azure DevOps/Jenkins; Terraform/Bicep/CloudFormation.
Monitoring/Observability: Prometheus/Grafana, cloud-native monitors, logging, data quality monitors, model monitoring.
Proven experience embedding security/privacy-by-design and RAI principles into delivery and ops.
Excellent stakeholder management, vendor management, and executive communication skills.
Certifications (nice-to-have): PMP/Prince2, CSM/SAFe, Azure/AWS/GCP data/AI, Databricks/Snowflake, Governance/Privacy.
Skills: Category Name Required Importance Experience
SkillCategoryTest1_MN Digital : Machine Learning Yes 1 7+ years