Work Location:Toronto, Ontario, Canada
Hours:37.5
Line of Business:Technology Solutions
Pay Details:$96,900 - $136,800 CAD
This role is temporarily eligible for a pay premium above the posted salary range that is reassessed annually. You are encouraged to have an open dialogue with your recruiter who can provide more specific pay details for this role.
Job Description:Department Overview:The Treasury Analytics Group is responsible for measuring and managing market risk, including interest rate and foreign exchange risk, across the Bank's retail portfolios. The team develops financial models and processes to support risk measurement, transfer pricing, hedging, product profitability analysis, and financial management reporting.
The Treasury Analytics Group is enhancing its existing data platform in TD's Azure Cloud to support next-generation capabilities for risk, valuation, and analytics while meeting the department's growing future needs. This role offers the opportunity to work with modern technologies, including Azure PaaS, Azure Databricks, Delta Lake, HBase, Cosmos DB, and MongoDB, to help the business gain deeper insight into portfolios and valuation metrics.
As technology continues to evolve, the Treasury Analytics Group is modernizing its data platform and adopting cloud-native engineering practices. We foster an innovative and collaborative environment that encourages ownership, technical excellence, and continuous improvement while using modern Azure and data technologies to shape the future of Treasury Analytics.
Reporting to the Senior Manager of Data Platform, the
Senior Cloud Development Lead will lead the design, development, and delivery of modern data platform capabilities across Azure Cloud and legacy on-premises big data platforms. The successful candidate will provide hands-on technical leadership for Treasury Analytics solutions, with a focus on Azure Databricks, ADLS Gen2, Azure SQL, MongoDB, Spark-based data engineering, and modernization from Hadoop-based ecosystems.
We are looking for a proven engineering leader who can define end-to-end solution architecture, guide implementation teams, and take accountability for technical design, delivery quality, production readiness, and platform modernization. This role requires strong experience building scalable data pipelines and services using Azure Databricks, Apache Spark, Java/Spring Boot, HBase, and cloud-native data services.
KEY ACCOUNTABILITIES:- Lead the architecture, design, and delivery of cloud-native data platform solutions using Azure Databricks, ADLS Gen2, Azure SQL, MongoDB, Delta Lake, and related Azure PaaS services.
- Provide hands-on technical leadership for Spark-based data ingestion, transformation, aggregation, and serving patterns across batch and near-real-time workloads.
- Guide modernization and migration from Hadoop-based platforms, including Cloudera or Hortonworks, HDFS, Hive, Spark, and HBase, to Azure-based lakehouse architecture.
- Set technical direction for platform components, data models, integration patterns, CI/CD, resiliency, observability, and production readiness.
- Collaborate with business stakeholders, architects, data engineers, application teams, and platform partners to translate business objectives into scalable technical solutions, actionable delivery plans, and measurable outcomes.
- Lead backlog refinement, sprint planning, design reviews, code reviews, and technical decision-making while promoting Agile engineering practices.
- Drive engineering excellence through automation, reusable frameworks, DevOps practices, performance tuning, security controls, and operational reliability.
- Mentor developers and data engineers on cloud development, Spark optimization, Lakehouse design, and software engineering best practices.
- Own end-to-end technical delivery for assigned workstreams, ensuring solutions are secure, scalable, maintainable, and aligned with enterprise architecture standards.
- Collaborate with infrastructure, security, data governance, and operations teams to ensure platform services meet enterprise controls and production support expectations.
- Review technical designs, data models, integration patterns, and implementation approaches to identify risks, remove blockers, and align solutions with business outcomes and non-functional requirements.
- Lead troubleshooting and performance optimization for complex data pipelines, Spark jobs, Databricks workflows, SQL workloads, NoSQL access patterns, and production incidents.
- Represent the development team in architecture forums, release discussions, risk reviews, and senior stakeholder updates, clearly communicating delivery status, technical decisions, dependencies, and trade-offs.
EXPERIENCE & EDUCATION- Undergraduate degree, technical certificate, or equivalent practical experience.
- Preferred Bachelor's degree in Computer Science, Engineering, or a related technical discipline, or equivalent practical experience
- 7+ years of relevant technology experience, including hands-on software engineering, data engineering, solution design, and technical leadership for complex enterprise platforms.
- Strong Java development experience, including Spring Boot, Spring Data, RESTful services, microservices architecture, security integration, and production-grade application design.
- Experience designing and delivering large-scale data pipelines, lakehouse solutions, metadata-driven processing frameworks, and data serving layers for analytics and business applications.
- Experience with engineering tools and delivery practices such as Git, Maven, Gradle, Jenkins, Nexus, CI/CD pipelines, automated testing, code quality controls, and secure deployment practices.
- Proven ability to lead technical teams, influence architecture decisions, manage delivery risks, and communicate effectively with senior technology and business stakeholders.
- Hands-on experience with Azure Databricks, including workspace development, cluster configuration, job orchestration, notebook development, workflows, and secure integration with Azure services.
- Strong working knowledge of ADLS Gen2, including storage account design, data lake folder structures, access controls, encryption, lifecycle management, and integration with Databricks and downstream consumers.
- Strong Azure SQL development skills, including schema design, stored procedures, query tuning, indexing strategies, data loading patterns, and integration with batch and analytical workloads.
- Strong MongoDB skills, including document modeling, collection design, indexing, aggregation pipelines, access patterns, performance optimization, and operational considerations for enterprise workloads.
- Strong Apache Spark development skills using Java, Scala, or Python, including reusable data processing frameworks, performance optimization, large-volume data processing, and troubleshooting distributed workloads.
- Hands-on experience with Hadoop ecosystem components, including HDFS, Hive, YARN, Spark, HBase, Kerberos-secured clusters, and development or administration on Cloudera or Hortonworks platforms.
- Strong HBase skills, including table design, row key strategy, column family design, scan and get patterns, bulk loading, performance tuning, and integration with Spark or Java-based applications.
- Experience applying secure software development practices, including secrets management, identity and access controls, vulnerability remediation, audit readiness, and adherence to enterprise technology standards.
- Demonstrated ability to lead developers through design, build, testing, release, production support, incident resolution, and continuous improvement in a large enterprise environment.
- Experience leading modernization from on-premises Hadoop or HBase platforms to Azure Databricks, Delta Lake, ADLS Gen2, Azure SQL, MongoDB, or other cloud-native data services.
- Experience with lakehouse data modeling, data governance, Unity Catalog, Databricks SQL, workflow orchestration, and production support for enterprise analytics platforms.
- Azure, Databricks, MongoDB, or big data platform certifications are considered an asset.
- Experience with financial services, risk platforms, valuation analytics, regulatory reporting, or other high-volume data processing environments is preferred.
Additional Information: Join in on what others in TD Technology Solutions are doing:
- Inspire a positive work environment and help champion quality, innovation, teamwork, and service to the business.
- Learn voraciously, stretch your thinking, share your knowledge, and educate others.
- Communicate and collaborate with both technical and non-technical professionals.
- Cultivate winning relationships by building trust with business and technology partners.
- Share our commitment to productivity, effectiveness, and operational efficiency.
- Embrace change and witness amazing things happen - from the inside.
Language Requirement (Quebec only):Sans Objet
