Senior Technical Product Manager
Toronto, ON, CA, M5J 2V5 Toronto, ON, CA Vancouver, BC, CA
Description
Our team and what we'll accomplish together
Join our innovative Data Products team at TELUS, where we're transforming how we leverage customer insights to deliver exceptional experiences across our Employer ecosystems. As part of the Digital Experiences organization, we're building the next generation of data-driven products that put privacy and consent at the forefront while unlocking powerful value-added team member population clinical insights and business value.
Our team sits at the intersection of data engineering, product strategy, and customer experience. We work collaboratively across engineering, data science, privacy, legal, and business stakeholders to build scalable data products that respect customer privacy while delivering actionable insights. Together, we'll establish TELUS as a leader in ethical data practices and customer-centric product development.
What you'll do
- Lead the end-to-end product lifecycle for customer insights data products, from ideation through launch and optimization
- Define product vision, strategy, and roadmap for data products serving internal stakeholders and external partners
- Collaborate with data engineers, data scientists, and architects to design scalable, secure, and performant data pipelines and platforms
- Champion privacy-first product development by embedding data consent mechanisms into products from the ground up
- Design and implement consent management frameworks that comply with privacy regulations (PIPEDA, GDPR, CCPA) while optimizing for user experience
- Build and scale a comprehensive customer insights platform for reseller partners with robust metrics, KPIs, and analytics capabilities
- Design API strategies and data sharing mechanisms that balance insight delivery with privacy protection
- Partner with legal, privacy, and compliance teams to ensure all data collection and usage practices meet regulatory requirements
- Establish feedback loops with reseller partners to continuously improve the insights platform
- Support and mentor junior team members, providing guidance and coaching to drive successful product outcomes
Qualifications
What you bring
- 7+ years of product management experience, with at least 3 years in technical product management or data product roles
- Proven track record of launching and scaling data products, analytics platforms, or customer insight solutions
- Strong technical foundation with understanding of data architectures, APIs, databases, data pipelines, and cloud platforms (GCP, AWS, or Azure)
- Deep knowledge of data privacy regulations (PIPEDA, GDPR, CCPA) and experience implementing privacy-by-design principles
- Experience with consent management platforms and privacy-preserving data practices
- Demonstrated ability to work with SQL, understand data models, and perform data analysis
- Bachelor's degree in Computer Science, Engineering, Business, or related field (or equivalent experience)
- Excellent stakeholder management skills with ability to influence without authority across multiple teams
- Strong analytical and problem-solving skills with data-driven decision-making approach
- Outstanding communication skills with ability to articulate complex technical concepts to non-technical audiences
Experience with:
- B2B or B2B2C product models, particularly in telecommunications, insurance, or benefits industries
- Building products for reseller, partner, or channel ecosystems
- Customer data platforms (CDPs), data warehouses, or business intelligence tools
- API product management and developer experience design
Great to have:
- Advanced technical credentials including Master's degree (Computer Science, Data Science, MBA) or relevant certifications (CIPP, Product Management, GCP/AWS certifications)
- Domain expertise in employer benefits, telecommunications, health and wellness, or insurance sectors with understanding of reseller/channel partner ecosystems
- Data science and advanced analytics background with hands-on experience in ML methodologies and ability to translate data science capabilities into product features