Title: Director, Data Engineering, International Banking, Toronto, Mexico, Colombia, Peru
Requisition ID: Join a purpose driven winning team, committed to results, in an inclusive and high-performing culture.
Role
The Director, Data Ops is a senior technology leadership role accountable for the operational excellence, reliability, security, scalability, and cost efficiency of the Azure Databricks platform and related data operations across Mexico, Caribbean, Chile, Peru, and Uruguay.
This role leads a distributed team responsible for production data pipeline operations, CI/CD enablement, platform onboarding, observability, incident management, governance controls, and continuous improvement of the Lakehouse operating model. The Director will partner closely with Data Engineering, Architecture, Platform Engineering, Cybersecurity, Risk, Compliance, and business stakeholders to ensure Databricks-based data products are delivered safely, reliably, and in alignment with regional priorities and enterprise standards.
Is this role right for you? In this role you will:
Regional Leadership & Team Management
Lead, coach, and scale a regional Data Ops organization across Mexico, Caribbean, Chile, Peru, and Uruguay, with clear accountability for production operations, engineering discipline, service reliability, and continuous improvement.
Define operating objectives, performance expectations, delivery metrics, and talent development plans for engineers, operations leads, and platform support roles.
Coordinate priorities across countries, time zones, and partner teams, ensuring transparent execution, consistent standards, and timely escalation of risks, blockers, and service-impacting issues.
Data Ops Strategy, Operating Model & Execution




Define and implement the Data Ops operating model for Azure Databricks, including platform onboarding, environment management, release controls, production support, change management, and operational governance.
Drive automation across the data delivery lifecycle, including CI/CD pipelines, infrastructure-as-code, automated testing, deployment gates, code promotion, rollback patterns, and release traceability.
Establish and monitor service-level objectives for data pipelines and platform operations, including availability, data freshness, latency, job success rates, incident response, recovery time, and data quality.
Databricks Platform Operations & Reliability
Own the operational readiness of Azure Databricks workspaces, clusters, jobs, workflows, notebooks, libraries, secrets, service principals, and production deployment patterns.
Partner with Platform Engineering and Architecture to define secure, scalable workspace patterns, environment separation, cluster policies, runtime standards, capacity planning, and platform guardrails.
Build a strong observability practice for pipelines and platform services, including monitoring, alerting, logging, operational dashboards, root-cause analysis, and problem management.
Oversee the design, deployment, and optimization of cloud-based data infrastructure supporting Azure Databricks, including secure connectivity, storage integration, workload isolation, and scalable compute patterns.




Lead Fin Ops discipline for Databricks workloads, including cost transparency, tagging, budget controls, rightsizing, auto-termination, utilization reporting, capacity forecasting, and optimization of compute spend.
Ensure compliance with enterprise cloud, cybersecurity, privacy, data residency, and regulatory requirements, coordinating with control functions and regional stakeholders as needed.
Governance, Security & Data Controls
Define and enforce governance practices for Databricks and lakehouse assets, including Unity Catalog adoption, access management, data lineage, auditability, ownership models, and production data controls.
Establish secure operating patterns for service principals, secrets management, privileged access, setting segregation, and production job execution.
Partner with Cybersecurity, Risk, Compliance, and Architecture teams to ensure controls are embedded early in the delivery lifecycle and continuously validated through operational reporting.
Stakeholder Engagement & Operational Excellence
Serve as the operational owner and escalation point for Databricks Data Ops across regional, global, platform, architecture, security, and business stakeholder groups.
Communicate operational health, delivery progress, risks, incidents, remediation plans, platform dependencies, and investment needs to senior leadership.
Establish executive-ready KPIs and dashboards covering platform adoption, pipeline reliability, SLA performance, data quality, incidents, cost efficiency, onboarding progress, and engineering productivity.
Stay current with Databricks, Azure, Data Ops, Dev Sec Ops, Fin Ops, observability, and data engineering practices, translating relevant capa

📌 Director, data engineering, international banking, toronto, mexico, colombia, peru
🏢 Scotiabank
📍 Toronto