Data Product Manager — Analytical Data Products (Hybrid)

Medium; Toronto (OH); Hybrid; USD 92,420 - 113,748; Full time

Benefits offered by this job

Hybrid flexibility

Health, dental, and vision insurance

Learning & growth opportunities

Job summary

ShyftLabs in Toronto is seeking a Data Product Manager to own the strategy, roadmap, and delivery of analytical data products for client projects. You will collaborate with engineering, analytics, and architecture teams to translate complex business challenges into scalable data solutions.

The ideal candidate has 3–5+ years in product management, strong SQL skills, and hands-on experience with modern cloud data platforms such as Snowflake, BigQuery, and Databricks.

Qualifications

• Bachelor's degree in Computer Science, Data Science, Information Systems, Business, Engineering, or a related discipline.
• 3‑5+ years of experience in Product Management, Data Product Management, Data Management, Analytics, or Data Science.
• Proven experience managing the full product lifecycle from discovery through launch and continuous improvement.
• Strong client‑facing experience with the ability to gather requirements, influence stakeholders, and manage expectations.
• Advanced SQL skills with the ability to analyze datasets and validate business hypotheses.
• Experience working with modern cloud data platforms such as Snowflake, BigQuery, ClickHouse, Databricks, Redshift, or similar technologies.
• Working knowledge of: Data governance, Semantic layer concepts, FAIR principles, Modern data architecture patterns.
• Experience working within Agile product development environments.
• Excellent communication and presentation skills with the ability to explain complex technical concepts to both technical and non‑technical audiences.

Responsibilities

• Own the end-to-end lifecycle of analytical data products, from discovery and roadmap planning through delivery, adoption, and continuous improvement.
• Define product vision and priorities aligned with client business objectives and organizational strategy.
• Balance new feature development with technical debt reduction, platform scalability, and long-term product sustainability.
• Monitor product performance and usage metrics to identify opportunities for optimization and future enhancements.
• Serve as the primary client-facing product lead throughout product delivery.
• Lead discovery workshops, requirements gathering sessions, and solution scoping discussions.
• Translate business objectives into clear product requirements and prioritized development backlogs.
• Build trusted relationships with client stakeholders by communicating technical concepts in a clear, business-focused manner.
• Manage stakeholder expectations while balancing competing priorities across multiple initiatives.
• Maintain, prioritize, and refine product backlogs based on evolving business needs.
• Partner with Engineering, Analytics, Architecture, and Data teams to deliver scalable analytical data products.
• Lead Agile ceremonies including sprint planning, backlog refinement, stand‑ups, retrospectives, and release planning.
• Ensure successful product launches and ongoing operational excellence.
• Collaborate with engineering teams to define data quality, governance, testing, and usability standards.
• Contribute to architectural discussions involving modern data platforms including Snowflake, BigQuery, ClickHouse, and similar technologies.

Skills

SQL analysis

Client-facing

Agile

Data storytelling

Communication

Education

Bachelor's degree in CS/Data Science/IS/Engineering/Business

Master's degree (nice to have)

Tools

Snowflake

BigQuery

ClickHouse

Databricks

Redshift

Job description

ShyftLabs in Toronto is seeking a Data Product Manager to own the strategy, roadmap, and delivery of analytical data products for client projects. You will collaborate with engineering, analytics, and architecture teams to translate complex business challenges into scalable data solutions.

The ideal candidate has 3–5+ years in product management, strong SQL skills, and hands-on experience with modern cloud data platforms such as Snowflake, BigQuery, and Databricks.