Location & FlexibilityOur
Director & Practice Lead, Data Engineering will operate remotely in Canada OR be based out of either our Toronto, ON or Vancouver, BC office locations.
The OpportunityTELUS Digital's Data, AI & Cloud (DAIC) practice is the multidisciplinary engine behind enterprise AI, blending boutique innovation with the breadth of a global services portfolio to help organizations architect, scale, and secure their transformations. Spanning our full family of specialized capabilities, the DAIC practice delivers end-to-end solutions across AI Advisory, AI Solutions, Data & AI Platforms, and Cloud Transformation.
As a premier Google Cloud partner, our Cloud practice is at the forefront of helping enterprises adopt and scale on Google Cloud infrastructure: delivering complex engineering, deployment, and migration programs for some of the largest organizations in Canada and beyond.
The
Director & Practice Lead, Data Engineering will define and own the Data Engineering Practice along with its market positioning, P&L, talent, and the quality of work we deliver for clients. This role is for someone who has led data and AI practices before, understands how to turn messy enterprise data estates into strategic assets, and earns trust with C-suite executives through genuine expertise. You will shape how we help clients move from data ambition to durable, AI-ready infrastructure.
This role will have four core anchor responsibilities:
- Strategy: Set the practice vision and align Data & AI capabilities to where enterprise demand is heading.
- P&L: Own revenue targets, margin, and growth while being accountable for the practice's full commercial performance.
- Talent & Culture: Build a practice where data-driven thinking, innovation, and engineering rigour are the baseline.
- Client Impact: Act as a trusted advisor to enterprise CxOs navigating data strategy, AI adoption, and governance.
Responsibilities- Define the multi-year vision for the Data Engineering Practice, ensuring our technical capabilities are ahead of the curve for enterprise demand for Data & AI transformation.
- Own the full P&L, including pipeline, pricing, delivery margin, and revenue growth, while reporting directly to executive leadership with clear commercial accountability.
- Build and sustain senior relationships with Google Cloud partner teams and client executives to generate meaningful deal flow and expand strategic accounts.
- Lead the practice's position on ethical AI and data democratisation while making principled, evidence-based bets on where advanced analytics and AI are creating real enterprise value.
- Drive investment in reusable IP, data accelerators, and delivery assets that improve consistency, reduce time-to-value, and protect margins at scale.
- Serve as a strategic advisor to client C-suite executives, helping them define data strategy, navigate AI adoption, and build the organisational capabilities to sustain it.
- Set the standard for engineering and analytical excellence across the practice by hiring well, developing talent deliberately, and building teams that clients trust and return to.
Competencies- 12+ years in data or AI consulting, including at least 3-5 years in a practice leadership or executive role, not just senior delivery or individual contribution.
- Proven P&L ownership: Direct experience managing revenue, margin, and growth targets in a consulting or professional services context.
- Data and AI ecosystem depth: Strong command of modern data architecture, AI, and ML trends, cloud-native data platforms, and enterprise data governance.
- Executive communication: Able to advise, challenge, and build lasting trust with C-suite stakeholders on complex, ambiguous problems, not just present to them.
- Business Development track record: Experience generating pipeline and closing complex, multi-stakeholder engagements, not just managing delivery once work is sold.
- Talent leadership: Has hired, grown, and retained senior data engineering and consulting talent in a practice or delivery organisation.
