Lead Data Engineer

Valtech

Lead Data Engineer shaping high-value data architectures for Valtech's data platform. Delivering client-focused solutions in data analytics and AI-based systems.

Posted 7/6/2026full-timeRemote • 🇨🇦 CanadaSenior💰 CA$110,000 - CA$150,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates deep expertise in data architecture, including conceptual, logical, and physical data modeling, while effectively connecting business goals with semantic structures and governance expectations. Proven ability to influence stakeholders and elevate quality across teams through strong communication and advisory skills.

Highest-signal resume keywords

Data Architecture ExpertiseConceptual, Logical, And Physical Data ModelingGovernance Direction And StandardsSemantic Layer DesignStakeholder Advisory Skills

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data ArchitectureData ModelingSemantic ConsistencyBusiness Entity DesignMetadata ManagementAnalytics SupportMachine Learning IntegrationAI Workflow DesignTaxonomy And Ontology DesignGoverned Access Patterns

Soft Skills

Analytical Problem-SolvingExecutive CommunicationCollaboration Across TeamsWorkshop FacilitationInfluencing Senior Audiences

Industry Keywords

Enterprise Data PlatformData GovernanceData QualitySemantic FrameworksReference ArchitecturesBusiness Concept FrameworksData ProductsAgentic SystemsDistributed TeamsHigh-Visibility Business Environments

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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.

Benefits

Comp & perks

A comprehensive insurance plan, where you can choose the module that best suits your needs—Gold, Silver, or Bronze. The employer may contribute up to 80% of your coverage depending on the selected module. This plan includes short- and long-term disability coverage.
Dialogue via Sun Life provides virtual healthcare services, allowing you to consult with a healthcare professional for emergencies, prescription renewals, and more. You also have access to the Employee and Family Assistance Program, as well as a complete mental health support program.
A $500 Personal Spending Account, which can be used for healthcare reimbursements, gym memberships, public transit passes, office supplies, or contributions to your RRSP through Valtech.
A retirement plan where Valtech will match 100% of your RRSP contributions through a Deferred Profit Sharing Plan (DPSP), up to a maximum of 4%. You can start contributing to your RRSP immediately, and to the DPSP after 3 months. The vesting of the DPSP will be after a 24 months of service.
Access to a flexible vacation under Valtech's policy to support your work-life balance, with 5 days available during your probation period and a prorated amount calculated for the remainder of the year.
Personal Technology Reimbursement – $30/month for every employee-offered on day 1.
We close during the winter holidays and offer flexible scheduling throughout the year, so you can enjoy those sunny Friday afternoons—provided your weekly hours are completed.