Product Manager - Data Platform
New
Remote or MississaugaFull-TimeMiddle
Salary$109,400 - $121,500 a year + bonus + benefits
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Job Details
- Experience
- 3+ years
- Required Skills
- PythonSQLProduct ManagementData modelingDatabricks
Requirements
- Bachelor's degree in Healthcare, Engineering, Business Administration, or related field.
- 3+ years of product management experience, including B2B experience with enterprise customers.
- Experience managing software or platform products through the full development lifecycle.
- Experience working with data platforms, data pipelines, or analytics products.
- Strong understanding of data concepts such as data modeling, schema design, and data transformation.
- Familiarity with Azure (Data Lake), Databricks, or comparable cloud data platforms.
- Working knowledge of SQL and/or Python (preferred).
- Experience with data cataloging, governance, and cross-domain data definition.
- Ability to influence and drive alignment across engineering, data, and product stakeholders.
- Strong communication and stakeholder management skills with both technical and business audiences.
Responsibilities
- Own the roadmap and backlog for your portfolio, prioritizing datasets and platform capabilities against customer value and business impact.
- Serve both customers and internal data stakeholders, translating domain needs into clear data definitions, schemas, and requirements.
- Run continuous discovery with domain experts and engineering teams to deeply understand data sources, transformations, and usage across the platform.
- Partner with data platform engineers to guide datasets through transformation stages, ensuring quality progression into trusted, consumable data layers.
- Work cross-functionally with engineering, analytics, and product teams to enable consistent and scalable data usage across the platform.
- Define and monitor data health, adoption, and usability metrics, using insights to inform roadmap decisions.
- Enable and support data catalog creation and ongoing maintenance, ensuring datasets are well-documented and understood across teams.
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