Lead Data Engineer

Valtech

2d • CA$110,000 - CA$150,000 • Onsite

About The Position

As a Lead Data Engineer, you will help clients define the foundations that power modern analytics, AI, and agentic systems. You will influence executive stakeholders, shape architecture strategy across complex organizations, and drive the evolution of enterprise-scale data ecosystems. This role is responsible for shaping high-value data architecture strategies, defining scalable semantic and platform-aligned design approaches, advising senior stakeholders, and elevating the quality and consistency of architecture delivery across engagements. The Lead Principal operates as a trusted authority in business entity design, semantic structure, governance direction, platform architecture, and the structural foundations that support reporting, analytics, machine learning, AI, and agentic systems. At this level, the role combines senior architecture leadership, strong business advisory capability, and broad influence across teams, clients, and practice development efforts.

Requirements

• 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, ambiguous, and high-visibility business environments.
• Expert ability to connect business context, semantic structure, governance direction, platform realities, and downstream analytical and AI needs in a way that is clear, credible, and actionable.
• Strong command of business entities, dimensions, metrics, domains, lineage, metadata, semantic consistency, governed access concepts, and reusable reference patterns.
• Strong understanding of semantic layers, business concept alignment, taxonomy and ontology-informed design, and domain-oriented architecture thinking.
• Strong awareness of how architecture choices support reporting, analytics, data science, machine learning, AI workflows, retrieval patterns, and agentic systems.
• Strong analytical and problem-solving skills across model complexity, semantic ambiguity, governance tradeoffs, platform decisions, and downstream usability concerns.
• Ability to provide design authority and architectural clarity without needing direct ownership of every implementation detail.
• Advanced stakeholder advisory skills, including executive communication and the ability to influence senior audiences.
• Ability to elevate quality and consistency across multiple teams without direct authority.
• Strong written and verbal communication skills in English, including workshop facilitation, executive presentation, and strategic advisory communication.
• Ability to collaborate effectively across distributed teams in the Americas and across multiple disciplines.
• Fluency in English is necessary for Québec-based candidates due to collaboration with teams in the Americas and Europe.

Nice To Haves

• Experience with taxonomy, ontology, and knowledge-modeling approaches.
• Exposure to Unity Catalog, Collibra, or similar governance solutions.
• Working knowledge of SQL, dbt, Python, Spark, or modern data engineering practices.
• Databricks, Azure, or Google Cloud certifications.
• Experience contributing to pre-sales, solution architecture, or thought leadership activities.
• Experience defining AI-ready or agentic-ready enterprise architectures.

Responsibilities

• 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.

Benefits

• Comprehensive insurance plan (Gold, Silver, or Bronze options with up to 80% employer contribution), including short- and long-term disability coverage.
• Virtual healthcare services via Dialogue through Sun Life for emergencies, prescription renewals, etc.
• Employee and Family Assistance Program.
• Complete mental health support program.
• $500 Personal Spending Account for healthcare reimbursements, gym memberships, public transit passes, office supplies, or RRSP contributions.
• Retirement plan with 100% Valtech match on RRSP contributions up to 4% through a Deferred Profit Sharing Plan (DPSP).
• Flexible vacation policy with 5 days available during probation and prorated amount for the remainder of the year.
• $30/month Personal Technology Reimbursement from day 1.
• Paid winter holidays.
• Flexible scheduling.

What This Job Offers

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