Gestionnaire de produit - données / Data Product Manager

PayFacto•Montreal, QC

19d

About The Position

We are currently seeking a Data Product Manager to join our team. This role leads the strategy, roadmap, and delivery of a modern AWS-based data platform that powers internal financial reporting, hospitality POS analytics, and payments insights across the organization. The platform serves both internal users and is also externalized to support customer-facing data products and experiences. This position combines end-to-end data product ownership with deep technical collaboration, ensuring stakeholders have access to trusted, well-governed data to support decision-making.

Requirements

Experience with AI/ML workflows (training pipelines, feature engineering, model serving, MLOps).
Ability to define and manage AI-ready data products (labeled datasets, feature stores, embeddings, vector databases).
Familiarity with LLM applications, prompt engineering, and RAG architectures.
Understanding of AI governance (explainability, bias detection, data drift, responsible AI).
Experience integrating AI-driven analytics or generative AI into data products.
Ability to evaluate AI/ML platforms (e.g., SageMaker, Azure ML, Vertex AI, Databricks ML).
Strong data literacy across the full data lifecycle.
Hands-on experience with cloud and data platforms (Databricks, Snowflake, AWS, Azure, GCP).
Knowledge of data governance, metadata, lineage, and integration frameworks.
Strong product management fundamentals (roadmapping, backlog management, stakeholder alignment, metrics-driven decisions).
Degree in Computer Science, Engineering, Information Systems, or equivalent experience.
Deep knowledge of data platforms, AWS ecosystem, and modern data/AI practices (DataOps, MLOps).
Ability to collaborate closely with engineers and data scientists.

Nice To Haves

Experience with AI/ML or data-intensive products preferred.
Proven track record managing data platforms or technical products.
Experience working in cross-functional teams and delivering at scale.
Strong prioritization and execution skills in agile environments.
Excellent communication, storytelling, and stakeholder influence.
Collaborative mindset with the ability to drive clarity and momentum.
Strong understanding of AI infrastructure and its business alignment.

Responsibilities

Define and evolve the product vision, strategy, and roadmap for the enterprise data platform (data lake/warehouse, shared data services, AI/ML data foundations).
Translate business and analytics needs into platform capabilities (data sharing, governance, integration, self-service) and prioritize the product backlog accordingly.
Partner with engineering, architecture, and data science teams to design and deliver scalable platform features (ingestion, transformation, cataloging, access control, APIs) using modern data technologies.
Drive adoption and internal customer satisfaction by gathering feedback, iterating on capabilities, and measuring platform value and impact.
Coordinate cross-functional launches, ensure operational readiness (documentation, training, support), and oversee the full product lifecycle from concept to deprecation.
Champion AI readiness across the platform, ensuring pipelines, feature stores, and governance frameworks support ML model development, deployment, and monitoring.
Support the externalization of data products and platform capabilities to customers, including defining APIs, data feeds, and self-service experiences.
Collaborate across business units and stakeholders to align priorities, resolve dependencies, and deliver measurable value.
Own end-to-end delivery strategies, including scope, milestones, sequencing, and success criteria, while coordinating execution across squads.