Lead Data Engineer

The opportunity

At Valtech, you’ll find an environment designed for continuous learning, meaningful impact, and professional growth. Whether you're pioneering new digital solutions, challenging conventional thinking or building the next generation of customer experiences, your work will help transform industries.

At Valtech, we're the Experience Innovation Company. We help leading global brands unlock value through data, AI, technology, and experience transformation.

As a Lead Data Engineer you'll help clients define the foundations that power modern analytics, AI, and agentic systems. You'll influence executive stakeholders, shape architecture strategy across complex organizations, and drive the evolution of enterprise-scale data ecosystems.

Please note, we are only accepting applicants from the provinces of Ontario and Québec for this role. For Québec-based candidates, fluency in English is necessary because the position entails collaboration with teams based in the rest of the Americas and occasionally in Europe.

• Lead the most complex and high-impact data architecture initiatives across clients, business areas, domains, platforms, or strategic programs.
• Define data architecture strategies that connect business goals, domain structures, semantic logic, platform realities, governance expectations, and downstream consumption needs.
• Serve as a senior advisor to internal and client stakeholders on architecture maturity, semantic structure, governance direction, platform-aligned design, and long-term maintainability.
• Establish and refine best practices for conceptual, logical, and physical data modeling, business entity design, semantic consistency, metric and dimension alignment, metadata expectations, domain boundaries, and reusable architecture patterns.
• Guide the design of scalable semantic structures, business concept frameworks, taxonomy and ontology-informed models, governed access patterns, and reference architectures that improve trust and downstream usability.
• Translate ambiguous executive and stakeholder questions into clear architecture approaches, semantic frameworks, platform strategies, governance-aligned design patterns, and business-relevant recommendations.
• Lead architecture reviews and design authority discussions to identify risks, resolve ambiguity, strengthen standards alignment, and improve long-term structural quality.
• Assess and shape how architecture choices support reporting, analytics, data products, machine learning, AI workflows, retrieval patterns, and agentic systems across structured, semi-structured, and selected unstructured data use cases.
• Provide governance direction through standards, design reviews, architecture guardrails, and decision frameworks while keeping hands‑on governance execution lighter than framework and review ownership.
• Synthesize architecture tradeoffs, semantic implications, platform constraints, and governance considerations into clear insights, strategic implications, and recommended actions.
• Influence cross-functional teams across DEPA, DSAI, and AIO to improve how data platforms, governed data products, semantic layers, analytics, and AI workflows work together.
• Review major architecture deliverables to ensure quality, clarity, consistency, rigor, and practical business value.
• Contribute to thought leadership, growth initiatives, proposal strategy, solution shaping, and new business efforts where senior architecture expertise is required.
• Help create, improve, and promote reusable frameworks, templates, standards, semantic models, reference architectures, design review patterns, and accelerators that strengthen delivery consistency across the practice.
• Mentor senior practitioners and help define what excellent data architecture practice looks like across the organization.
• Reinforce strong governance, privacy, security, and data‑quality expectations across engagements and teams.

To be considered for this role, you should have:

• Deep expertise in data architecture, enterprise data platform concepts, and conceptual, logical, and physical data modeling.
• Strong ability to shape data architecture approaches in complex,…