Manager, Data Engineering

Role Overview

• Build, develop, and retain high-performing Data Engineering / Software Engineering teams, ensuring the right mix of skills and behaviors
• Recruit key talent and evolve team composition as program phases and priorities shift
• Own end-to-end planning and delivery for complex initiatives: discovery, design/refactoring, build, test, release/cutover, and decommissioning as needed
• Establish scope, milestones, budgets, timelines, dependencies, and risk/issue management; maintain dashboards and KPIs
• Divide work into achievable tracks with clear roles and responsibilities, balance business needs with individual strengths and aspirations
• Provide technical leadership to the team, understanding the solutions and propose improvements and adjustments for efficiencies using modern technology
• Promote responsible AI usage to accelerate code understanding, refactoring, documentation, testing, and analytics—defining standards and guardrails for privacy, security, and validation
• Build strong relationships with product, architecture, security, finance, and business partners
• Communicate complex technical concepts and trade-offs clearly to technical and non-technical audiences, document and report progress
• Ensure governance adherence; proactively escalate risks and drive timely decisions
• Ensure adoption of best practices across data modeling, coding, version control, testing, observability
• Embed security and data governance (access controls, classification, privacy/compliance) into platforms and pipelines
• Promote communities of practice, knowledge sharing, and built-in quality; continually optimize processes and tools

Requirements

• Bachelor’s degree in information technology/software engineering or equivalent education and experience
• 10+ years across data engineering/analytics/AI/software engineering, with 5+ years leading large teams and complex initiatives
• Proven experience leading enterprise data platform programs and migrations between major DWH technologies (e.g., Oracle, Teradata, SQL Server) and modern cloud platforms (AWS, Snowflake, Databricks)
• Up to date with technology advancements and market trends in data platforms, analytics engineering, AI/ML tooling, and cloud services
• Understanding of: Data modeling (dimensional, data vault), orchestration (e.g., Airflow, Control M), CI/CD for data, data quality, and observability
• Modern data stack AI/LLM tools to accelerate development and analysis, with clear validation and governance practices
• Strong stakeholder management, influence, and communication skills; able to navigate ambiguity and drive cross-functional decisions
• Track record hiring, coaching, and leading large teams with high engagement, accountability, and inclusion
• For candidates located in Quebec, bilingualism is required (French and English): Need to interact on a regular basis with colleagues across the country.

Tech Stack

• Airflow
• AWS
• Cloud
• Oracle
• SQL
• Vault

Benefits

• Flexible work arrangements and a hybrid work model
• Possibility to purchase up to 5 extra days off per year
• Multiple benefits offered to support physical and mental wellbeing, including telemedicine, Wellness account and much more
• Share plan & other savings: up to 12% of salary or even more (ask how you could earn guaranteed income for life)
• Annual bonus target, based on the base salary, with a potential payout of up to double the target (subject to personal and company performance): 15%