PRACTICE LEAD DATA ANALYTICS AND VISUALISATION

We are banking at another level.

Choosing BDC as your employer means working in a healthy, inclusive, and skilled workplace that puts forward the best conditions to bring together unique teams where employees are empowered to act. It also means being at the centre of ambitious economic and financial projects to see further and to do things differently, to fuel the success of Canadian entrepreneurs.

Choosing BDC as your employer also means:

Flexible and competitive benefits , including an Employee Savings and Investment Plan where BDC matches part of your voluntary contributions, a Defined Benefit Pension Plan, a $750 wellness and health care spending account, to name a few

In addition to paid vacation each year, five personal days , sick days as necessary , and our offices are closed from December 25 to January 1

A hybrid work model that truly balances work and personal life

Opportunities for learning , training and development , and much more...

Explore the BDC Way in our Culture Book

POSITION OVERVIEW

BDC views data-driven decision-making as a strategic capability that must be embedded across all business lines and corporate functions. Reporting to the AVP, Data Analytics & AI, the Practice Lead, Data Analytics & Visualization is accountable for developing and leading BDC's enterprise analytics capability through a combined Chapter, Center of Expertise and Hub-and-Spoke mandate.

The incumbent acts as both a people leader and a capability leader. They lead, coach and develop Analytics Engineers, BI Developers, Data Visualization Specialists and Analytics Practitioners who may be deployed across data platform squads, business-facing initiatives and enterprise priorities. The role establishes the standards, talent practices, communities of practice and capability roadmap required to mature analytics delivery across BDC.

The role plays a dual mandate in BDC's operating model. As the enterprise analytics hub, the team influences and enables analytics practitioners across business lines and corporate functions by clarifying standards, delivering training, sharing best practices and supporting the safe adoption of self-service analytics. As a Chapter and Center of Expertise, the team develops analytics engineering, BI, visualization and semantic modelling capabilities while deploying expertise into data platform squads responsible for building analytical and semantic layers.

The incumbent owns the Analytics Engineering, BI & Insights Center of Expertise. In this capacity, the role defines reusable semantic model practices, trusted reporting standards, KPI and metrics guidance, Power BI and visualization guidelines, data storytelling practices and self-service analytics guardrails that help the organization make decisions with confidence.

The role influences the evolution of analytics platforms, semantic layers, reporting practices and decision intelligence capabilities in close collaboration with Product Development Managers, Architects, Delivery Leads, Data Governance, business analytics teams and technology stakeholders. The Chapter Lead does not own product delivery priorities, but is accountable for ensuring BDC has the skills, standards, communities and practices required to scale trusted analytics throughout the organization.

CHALLENGES TO BE MET

Leadership and capability chapter

• •Lead, coach and develop Analytics Engineers, BI Developers, Data Visualization Specialists and analytics practitioners deployed across squads, platforms and enterprise initiatives.
• •Establish the chapter mandate, capability roadmap, talent plan, community routines and performance expectations for the Analytics Engineering, BI & Insights discipline.
• •Assess current and future skills needs across analytics engineering, semantic modelling, enterprise reporting, Power BI, visualization, self-service analytics and data storytelling.
• •Create the conditions for analytics practitioners to scale expertise across teams rather than operating as isolated reporting resources.
• •Build a culture of trusted data use, analytical rigor, collaboration, knowledge sharing, continuous improvement and pragmatic delivery excellence.

Center of Expertise ownership

• •Own the Analytics Engineering, BI & Insights Center of Expertise, including standards, methods, guidance, reusable patterns, playbooks and maturity practices.
• •Define and evolve enterprise practices for semantic models, data marts, trusted metrics, dashboard design, reporting quality, visualization standards and data storytelling.
• •Clarify analytics standards, best practices and expected ways of working for business analytics teams and data platform squads.
• •Facilitate communities of practice that help practitioners share patterns, improve reporting quality and increase analytical maturity across BDC.
• •Zartner with Data Governance to ensure analytics practices support data quality, stewardship, privacy, security and consistent interpretation of enterprise metrics.

Enterprise analytics hub and business enablement

• •Operate the analytics capability as an enterprise hub that supports analytics teams across business lines and corporate functions.
• •Influence analytics practices across BDC by providing guidance, coaching, training, templates, standards and reusable assets to business analytics practitioners regardless of reporting line.
• •Develop and maintain training programs, office hours, playbooks and enablement materials that help business teams adopt trusted self-service analytics practices.
• •Provide advisory services to business lines and corporate functions on reporting approaches, KPI interpretation, dashboard design, visualization practices and analytical methods.
• •Promote consistency in reporting, metrics, business definitions and analytical methods while enabling business teams to retain autonomy for domain-specific needs.
• •Assess analytics maturity across BDC and develop capability-building initiatives that improve adoption, consistency, quality and analytical effectiveness.

Semantic layer and data platform squad enablement

• •Partner with Data Engineering Chapter Leads, Product Development Managers and data platform squads to define, develop and continuously improve analytical and semantic layers.
• •Ensure analytical data products are designed with business consumption, trust, usability, reusability, performance and self-service in mind.
• •Establish standards for semantic models, business metrics, dimensional modelling, certified datasets, data products and reusable analytical assets.
• •Influence the design of enterprise data products to maximize analytical value, business comprehension and consistency across domains.
• •Ensure alignment between enterprise reporting, semantic models, KPIs, business definitions and the data products delivered by platform squads.

Technical vision, roadmap influence and enterprise value

• •Influence analytics platform strategy, semantic layer direction, BI tooling practices, visualization standards and capability investments in partnership with PDMs, Architecture and platform leaders.
• •Provide senior technical guidance and decision support for analytics modernization, self-service BI, semantic model design and enterprise reporting initiatives.
• •Collaborate with PDMs, business partners and transformation leaders to translate business questions into trusted analytics capabilities and insight products.
• •Support prioritization discussions by clarifying data availability, semantic model implications, reporting quality considerations, technical dependencies and capability gaps.
• •Promote analytical literacy and data-driven decision-making by communicating complex data and analytics concepts in clear business terms.

WHAT WE ARE LOOKING FOR

• •Bachelor’s or master’s degree in business administration, computer science, engineering, data science, information systems, analytics or a related field, or equivalent work experience.
• •Significant experience in analyti