Senior Managing Consultant

Keyrus

. Partner with clients to understand business objectives, define transformation roadmaps, and architect scalable enterprise data solutions across Databricks, Microsoft Fabric, Snowflake, Azure, and complementary technologies.

Posted 11/9/2026full-timeMontreal • CanadaSenior💰 CA$130,000 - CA$160,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates extensive expertise in architecting and delivering modern enterprise data platforms, including scalable data pipelines and cloud-native analytics solutions. Proven ability to lead multidisciplinary teams, establish architectural standards, and drive technical pre-sales and solution design initiatives.

Highest-signal resume keywords

Data Engineering LeadershipEnterprise Data ArchitectureCloud-Native Analytics SolutionsTechnical Pre-Sales ExperienceMentoring and Capability Development

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Data Pipeline DesignLakehouse ArchitectureData Warehouse DevelopmentCloud ArchitectureTechnical Governance FrameworksModernization FrameworksAI Capabilities IntegrationPerformance OptimizationRisk ManagementDelivery Quality Management

Soft Skills

Client CollaborationTeam LeadershipMentoringStrategic Proposal DevelopmentCommunication

Tools & Technologies

DatabricksMicrosoft FabricSnowflakeAzure Data ServicesDbtDataOpsMLOps

Certifications & Qualifications

Cloud Architecture Certifications

Industry Keywords

Enterprise Data SolutionsTransformation RoadmapsData Engineering PracticeCommercial PerformanceGo-To-Market Strategy

Tech Stack

Tools & technologies

AzureCloudSnowflake

About the role

Key responsibilities & impact

Partner with clients to understand business objectives, define transformation roadmaps, and architect scalable enterprise data solutions across Databricks, Microsoft Fabric, Snowflake, Azure, and complementary technologies.
Lead end-to-end delivery of complex data engineering engagements, overseeing multidisciplinary teams, technical architecture, delivery quality, risk management, and commercial performance.
Define and govern architectural standards, reusable accelerators, modernization frameworks, and engineering best practices across the Data Engineering practice.
Lead and grow the Data Engineering practice by developing technical capabilities, mentoring consultants, and establishing consistent delivery standards.
Drive technical pre-sales, solution design workshops, strategic proposals, and go-to-market initiatives, developing differentiated offerings and industry-specific use cases.
Collaborate with strategic technology partners to align solution strategies, leverage emerging platform capabilities, and strengthen client offerings.
Champion the adoption of AI capabilities and emerging cloud and data technologies, translating innovation into practical solutions and measurable business outcomes.

Requirements

What you’ll need

8+ years of professional experience in Data Engineering, including 5+ years in Senior Consultant, Principal Consultant, Technical Lead, or Technical Project Management leadership roles.
Proven experience leading enterprise data consulting engagements, complex transformation initiatives, and multidisciplinary delivery teams.
Strong experience architecting and delivering modern enterprise data platforms, lakehouses, data pipelines, and cloud-native analytics solutions.
Experience establishing architectural standards, technical governance frameworks, and reusable engineering practices across multiple engagements.
Demonstrated experience leading technical pre-sales, solution design workshops, strategic proposals, and client-facing architecture discussions.
Experience mentoring consultants, developing engineering capabilities, and managing delivery quality, commercial performance, and client satisfaction.
Deep hands-on expertise in enterprise data architecture using Databricks, Microsoft Fabric, Snowflake, and Azure Data Services.
Strong experience designing scalable data pipelines, lakehouses, data warehouses, and cloud-native analytics platforms.
Proven ability to define and govern architecture standards across modern cloud and data ecosystems.
Experience developing modernization frameworks, reusable engineering accelerators, and technical governance models.
Strong understanding of delivery governance, risk management, performance optimization, and commercial considerations across concurrent engagements.
Experience enabling AI capabilities within enterprise data platforms and modern analytics ecosystems.
Strong technical leadership and solution design capabilities, with the ability to guide multidisciplinary engineering teams.
Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field is nice to have.
Microsoft Fabric, Databricks, Snowflake, Azure, or cloud architecture certifications are nice to have.
Experience with dbt and modern data transformation frameworks is nice to have.
Knowledge of DataOps, MLOps, and enterprise Data Governance strategies is nice to have.
Experience working with strategic technology alliances and partner ecosystems is nice to have.
Exposure to advanced AI-driven analytics, practice development, and go-to-market strategy is nice to have.

Benefits

Comp & perks

A stimulating environment where you can challenge yourself and discover new horizons.
A strong culture of innovation and entrepreneurship.
Opportunities to celebrate success through team activities, social events, and special celebrations.
Comprehensive group insurance for you and your family.
RRSP and DPSP participation plans.
Monthly wellness allowance.
Telecommunication reimbursement.
4 weeks of paid vacation.
Language courses (French and English).
Access to continuous learning through certifications, conferences, training programs, and industry events.
International mobility opportunities.