Director, Data Platform Engineering

TD•Toronto, ON

2d•CA$165,000 - CA$200,000•Onsite

About The Position

As the Director, Data Platform Engineering, you will define and execute the strategy, architecture, and engineering roadmap for the Global Transaction Banking (GTB) Data Platform. Built on Databricks, the platform serves as the foundation for next-generation data products, advanced analytics, AI-driven insights, regulatory reporting, and mission-critical transaction banking capabilities. You will lead high-performing engineering teams responsible for building secure, scalable, and resilient data solutions while establishing modern engineering practices, platform standards, and delivery excellence across the organization. This role requires a technology leader who combines deep expertise in data engineering and distributed systems with a passion for developing talent, driving innovation, and delivering business outcomes at scale. Mandate: Own the strategy, engineering delivery, and operational excellence of the GTB Data Platform, enabling trusted data, advanced analytics, AI innovation, and next-generation transaction banking capabilities through a modern Databricks-powered ecosystem.

Requirements

12+ years of progressive technology experience with significant experience leading large engineering teams and complex technology portfolios.
Proven success leading engineering managers, architects, and senior technical professionals.
Strong executive stakeholder management, communication, and influencing skills.
Experience managing budgets, strategic investments, vendors, and large-scale transformation initiatives.
Deep expertise designing, building, and operating enterprise-scale data platforms.
Extensive experience with Databricks, including platform architecture, engineering, optimization, governance, and operational management.
Strong experience with Apache Spark, Delta Lake, and large-scale distributed data processing frameworks.
Deep understanding of modern data architecture, data products, metadata management, lineage, governance, and data lifecycle management.
Experience building and scaling analytical, operational, and AI-ready data platforms.
Strong foundation in modern programming languages (Java, Python) and API design (REST, GraphQL).
Deep understanding of distributed systems, microservices, cloud-native architectures, and enterprise integration patterns.
Strong experience with Microsoft Azure and cloud-native platform delivery.
Experience with container orchestration (Kubernetes) and DevSecOps / CI/CD practices.
Proven experience building event-driven, real-time data architectures at enterprise scale.
Working knowledge of Generative AI, LLMs, and AI-enabled engineering practices.

Nice To Haves

Hands-on experience with streaming technologies such as Kafka, Confluent, Solace, or Apache Flink.
Familiarity with graph or document data models (Neo4J, MongoDB).
Experience with observability tooling such as Splunk, Dynatrace, or Datadog.
Exposure to OpenShift or other enterprise Kubernetes distributions.

Responsibilities

Define and execute the strategic roadmap for the GTB Data Platform, ensuring alignment with business objectives and enterprise technology strategy.
Lead the evolution of the Databricks platform, establishing a scalable, secure, and resilient foundation for analytics, data products, AI, and operational workloads.
Drive platform modernization, engineering transformation, automation, and AI-enabled development practices.
Establish engineering and data architecture standards, governance frameworks, and best practices for data, APIs, integration, and platform services.
Partner with business, product, architecture, security, infrastructure, and operations leaders to prioritize investments and accelerate business outcomes.
Lead multiple engineering teams responsible for data platforms, data products, APIs, streaming services, and cloud-native applications.
Oversee end-to-end delivery of strategic technology initiatives, ensuring quality, scalability, security, reliability, and operational excellence.
Provide technical leadership and oversight for architecture, system design, engineering standards, and modernization initiatives.
Drive engineering excellence through adoption of DevSecOps, CI/CD, automated testing, observability, reliability engineering, and platform engineering practices.
Act as the senior escalation point for critical engineering, platform, operational, and delivery issues.
Champion modern data architecture practices, including data products, event-driven architectures, real-time processing, and distributed computing.
Ensure effective governance, metadata management, lineage, data quality, and platform observability across the GTB ecosystem.
Drive adoption of data and AI capabilities that improve operational efficiency, customer outcomes, and business decision-making.
Promote reuse, standardization, and scalability of platform capabilities across GTB technology domains.
Accountable for platform investment planning, budget management, forecasting, and delivery performance.
Manage strategic vendor relationships and global delivery partners to achieve business and engineering objectives.
Establish governance processes, performance metrics, and operational controls to ensure transparency and predictable outcomes.
Identify and manage strategic technology, delivery, security, and operational risks.
Lead, coach, and develop engineering managers, architects, principal engineers, and senior technical talent.
Build a high-performing engineering organization focused on innovation, accountability, customer value, and technical excellence.
Drive workforce planning, succession management, capability development, and organizational growth.
Foster a culture of continuous learning, collaboration, ownership, and engineering craftsmanship.