Data Product Manager – Analytical Data Products in Toronto, Ohio at ShyftLabs

ShyftLabs is a fast-growing data and AI company that helps organizations unlock the value of their data through modern engineering, analytics, and intelligent products. We partner with Fortune 500 organizations to build scalable cloud solutions, AI-driven platforms, and innovative data products that accelerate business outcomes.

We're looking for a Data Product Manager to join our growing Data Products team. This role is ideal for someone who combines strong product management expertise with a deep understanding of modern data platforms and enjoys partnering directly with clients to translate complex business challenges into scalable analytical solutions.

Reporting to the Director of Analytical Data Products, you'll own the strategy, roadmap, and execution for a portfolio of analytical data products while serving as the primary point of contact for client stakeholders. You'll collaborate closely with engineering, analytics, and architecture teams to deliver high-quality, reusable data products that drive measurable business value.

• 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 closely 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.
• Advocate for reusable, scalable data products using modern architectural principles including Data Mesh, Data Fabric, Semantic Layer, and FAIR principles.
• Perform hands-on SQL analysis and data validation when necessary to support product decisions and client discussions.

• Partner with Legal, Privacy, Compliance, and Security teams to ensure products meet regulatory and governance requirements.
• Work closely with executive stakeholders to communicate product strategy, delivery progress, and technical tradeoffs.
• Foster a product-led culture focused on delivering measurable business value through data.

• 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.

• Master's degree in Engineering, Data Science, Business, or a related field.
• Experience within Pharma, Biotechnology, Financial Services, Consumer Packaged Goods (CPG), or Management Consulting.
• Familiarity with Customer Data Platforms (CDPs), Omnichannel Marketing, or Digital Marketing Analytics.
• Demonstrated experience using product usage metrics and customer insights to prioritize roadmap investments.
• Experience working with enterprise-scale data products serving multiple business units or external clients.