Lead the enterprise data strategy vision and roadmap, partnering closely with cross-functional teams to deliver prioritized initiatives on time.
Facilitate a multidisciplinary data strategy forum to drive key pillars and practices (i.e. platform and data architecture, data collection and management, data culture).
Develop and maintain a rolling plan with regular reviews, ensuring clear prioritization of lab-wide target capabilities and alignment with enterprise portfolio goals, IT initiatives, and regulatory requirements.
Produce and communicate strategic architecture deliverables that guide product-centric teams toward “north star” targets and provide strategic insights to senior leadership (i.e. capability assessments, market scans, target state definitions, roadmaps).
Participate in architecture peer reviews and serve as a trusted advisor, offering constructive feedback on data-related strategic directions and architecture best practices.
Requirements
Bachelor’s degree in information technology, Software/Data Engineering, Computer Science, or an equivalent combination of education and experience.
10+ years of significant experience in software engineering and/or data engineering assuming multiple roles (i.e. product manager, software developer, technical advisor, etc).
5+ years of experience in an application/solution/data architecture role leading large-scale data and/or ML/AI initiatives.
Proven delivery of data management capabilities (e.g., data architecture, modeling, storage, security, data quality).
Strong stakeholder engagement skills to facilitate decisions, resolve conflicts, and drive consensus.
Exceptional communicator who can distill complex strategic and technical concepts into clear, compelling messages for audiences from architects to the C‑suite.
Experience assessing current state across data domains and identifying gaps and opportunities.
Passion for defining and landing innovative ways to create, protect, share, and leverage data as an asset to enable better data-driven decisions for our customers.
Deep understanding of data needs to support AI product development at scale across the full lifecycle (e.g., data profiling, anonymization, observability, ML-Ops).
Strong knowledge of data management concepts (e.g., platform and data architecture, data collection and security at scale, data culture, AI capabilities, advanced analytics, data governance frameworks).
Proven expertise in data solution architecture, including reference architectures, conceptual modeling, and roadmap development for data platforms and products.
Experience evaluating vendors and platforms for architectural fit, security, and value.
Exposure levering modern data platforms & ecosystems (i.e., AWS, Databricks, Snowflake, etc).
Bilingual (French & English)
Need to interact on a regular basis with colleagues across the country.
No Canadian work experience required however must be eligible to work in Canada.
Tech Stack
AWS
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)