Senior Consultant, Data Developer

CIBC • Toronto, ON

8d • Hybrid

About The Position

We’re building a relationship-oriented bank for the modern world. We need talented, passionate professionals who are dedicated to doing what’s right for our clients. At CIBC, we embrace your strengths and your ambitions, so you are empowered at work. Our team members have what they need to make a meaningful impact and are truly valued for who they are and what they contribute.

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.

At CIBC we enable the work environment most optimal for you to thrive in your role. 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.

Requirements

• Deep Databricks and Spark expertise.
• Strong hands-on experience building and optimizing data engineering solutions with Databricks, Apache Spark, PySpark, Python, and SQL in cloud-based environments.
• Solution-focused technical leader who can turn complex business and analytics requirements into scalable, secure, and practical data solutions.
• Thoughtful design decisions and understanding of the trade-offs between speed, quality, cost, and risk.
• At least 4+ years of strong engineering and optimization skills.
• Understanding of distributed data processing, Data Lake, data lakes, lakehouse architecture, performance tuning, and pipeline optimization.
• Comfortable improving jobs, workflows, and platform performance across development and production environments.
• Experience with data quality practices, governance requirements, metadata management, and secure development approaches, including access controls and auditability.
• Clear communication with technical and non-technical partners.
• Effective collaboration across cross-functional teams.
• Enjoy mentoring developers to support strong delivery outcomes and shared engineering standards.
• Familiarity 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.
• Bring your real self to work and live our values of trust, teamwork, and accountability.

Nice To Haves

• Experience working in regulated environments such as banking or financial services is an asset.
• 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.

Responsibilities

• Lead the design, build, and maintenance of scalable ETL and ELT pipelines using Databricks, Apache Spark, PySpark, Python, and SQL.
• Develop reusable frameworks, utilities, and components that improve consistency, efficiency, and maintainability.
• 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.
• 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.
• 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.
• 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.
• 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.

Benefits

• Competitive salary
• Incentive pay
• Banking benefits
• Benefits program
• Defined benefit pension plan
• Employee share purchase plan
• Vacation offering
• Wellbeing support
• MomentMakers, our social, points-based recognition program
• Purpose Day; a paid day off dedicated for you to use to invest in your growth and development

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed