We’re building a relationship-oriented bank for the modern world. You’ll join a team focused on building modern, scalable data solutions that power analytics, reporting, and enterprise data transformation. As a Senior Consultant, Databricks Developer, you’ll lead the design, development, and optimization of data engineering solutions using Azure Databricks, Apache Spark, and cloud-based data services.

You’ll translate business and analytics needs into reliable technical solutions, supporting batch and near real-time data processing across complex environments. In this role, you’ll drive engineering excellence by improving performance, strengthening data quality and security controls, and contributing to architecture decisions across lakehouse and enterprise data platforms. You’ll also collaborate closely with architects, analysts, DevOps partners, and business stakeholders while mentoring junior team members and supporting successful delivery across the full development lifecycle.

You’ll have the flexibility to manage your work activities within a hybrid work arrangement where you’ll spend 1-3 days per week on-site, while other days will be remote. Design and development - Lead the design, build, and maintenance of scalable ETL and ELT pipelines using Databricks, Apache Spark, PySpark, Python, and SQL. Solution architecture - Translate business requirements into practical data solutions and contribute to architecture decisions across lakehouse, data warehouse, and enterprise integration environments.

Support the implementation of bronze, silver, and gold data layers and promote sound data modeling and storage practices. Performance optimization - Tune Spark jobs, Databricks clusters, notebooks, and workflows to improve scalability, reliability, and cost efficiency. Strengthen monitoring, logging, alerting, and error‑handling practices to support stable production operations.

Data quality and governance - Implement validation, reconciliation,



and data quality controls across pipelines and datasets. Ensure solutions align with enterprise expectations for governance, lineage, privacy, access control, and secure development practices. Delivery leadership - Partner with architects, analysts, data scientists, application teams, and business stakeholders to deliver complex data initiatives.

Review code, uphold engineering standards, provide technical guidance, and contribute to agile planning, estimation, releases, and production support. Continuous improvement - Investigate incidents, resolve defects, and perform root cause analysis to improve long-term platform health. Recommend enhancements to deployment pipelines, testing practices, and operational readiness that increase development productivity and solution resilience.

You have deep Databricks and Spark expertise. You bring strong hands‑on experience building and optimizing data engineering solutions with Databricks, Apache Spark, PySpark, Python, and SQL in cloud-based environments. You’re a solution‑focused technical leader.

You can turn complex business and analytics requirements into scalable, secure, and practical data solutions. You make thoughtful design decisions and understand the trade‑offs between speed, quality, cost, and risk. You understand distributed data processing, Data Lake, data lakes, lakehouse architecture, performance tuning, and pipeline optimization.

You’re comfortable improving jobs, workflows, and platform performance across development and production environments. You know how to build with control and care. You have experience with data quality practices,



governance requirements, metadata management, and secure development approaches, including access controls and auditability.

Experience working in regulated environments such as banking or financial services is an asset. You communicate clearly with technical and non‑technical partners, collaborate effectively across cross‑functional teams, and enjoy mentoring developers to support strong delivery outcomes and shared engineering standards. You’re familiar with orchestration and delivery tools such as Azure Data Factory, Feed Hub, Autosys Airflow, GitHub, Powershell Scripts and DevSecOps or CI/CD practices using GIT Hub Actions, Artifactory and Vaults experience with Structured Streaming, Unity Catalog, or machine learning pipelines on Databricks is considered an asset, Knowledge of Giene and Claude on Data Bricks is an Asset.

We work to recognize you in meaningful, personalized ways including a competitive salary, incentive pay, banking perks, a benefits program*, defined benefit pension plan*, an employee share purchase plan, a vacation offering, wellbeing support, and MomentMakers, our social, points‑based recognition program. You need to be legally eligible to work at the location(s) specified above and, where applicable, must have a valid work or study permit. We may ask you to complete an attribute-based assessment and other skills test (such as simulation, coding, French proficiency).

We use artificial intelligence tools during the recruitment process. Automation, Automation, Azure Data Factory, Cloud Platform, Collaboration, Database Modeling, Databricks Platform, Data Engineering, Data Governance, Data Integration, Data Lake, Data Pipelines, Data Solutions, Design, DevOps, DevSecOps, Enterprise Data, Enterprise Data Integration, Integration Solutions, Judgement, Microsoft Azure, Microsoft Azure Databricks, Performance Tuning, Problem Solving, Programming Languages {+ 4 more}

📌 Senior Training Developer/Consultant (Toronto)
🏢 CIBC
📍 Toronto