Technical Product Manager

Environics Analytics • Toronto, ON

16d • CA$95,000 - CA$115,000

About The Position

Reporting to the VP of Product Management for Media Activation & Data Collaboration Services (MDCS), the Technical Product Manager is a hands-on execution role responsible for building and delivering Environics Analytics’ (EA) data collaboration and AdTech platform products. This role translates product roadmap priorities into detailed technical requirements, drives feature development through the build cycle, and coordinates across engineering, media partners, and commercial teams to deliver on time and to spec. The ideal candidate brings a balance of technical depth, media industry knowledge, and business acumen – someone who can work through an API specification in the morning, speak credibly about campaign measurement with a broadcast client in the afternoon, and tie both back to a commercial outcome. AI-assisted workflows are central to how this team operates: we use large language models, agentic coding tools, and AI-powered productivity tools daily, and we expect this person to be proficient and intentional in how they leverage them.

Requirements

• Degree in Computer Science, Engineering, Information Systems, Marketing Technology or a related discipline. A combination of technical education and relevant industry experience will also be considered.
• 3–5 years in a product management role that required hands-on technical execution within AdTech, media technology, data platforms, or a related data-intensive domain.
• Direct experience writing technical specifications, defining API contracts, and working day-to-day with engineering teams through the build cycle.
• Demonstrated working knowledge of the media and advertising landscape—including at least two of: programmatic buying, broadcast/CTV, audience segmentation, campaign measurement/attribution, or retail media.
• Hands-on familiarity with at least two of: cloud data platforms (Azure, AWS, Snowflake), identity resolution systems (LiveRamp, UID2.0), clean room technologies, or consent management platforms.
• Working knowledge of Canadian privacy frameworks (PIPEDA, Law 25) as applied to data products and advertising systems.
• Experience with Agile/Scrum delivery in a software product environment.
• Proficient with AI-assisted work tools, including large language models and agentic coding assistants. Able to write effective prompts, evaluate AI-generated output critically, and integrate these tools into daily workflows for research, writing, analysis and technical problem-solving.
• Ability to read and reason re. SQL, JSON and API documentation. You don’t need to write production code, but you need to understand what the code does and why.
• Comfortable navigating cloud consoles (Azure Portal, Snowflake UI) and interpreting system telemetry, logs, and monitoring dashboards.
• Able to diagram and communicate data flows, system architectures and integration sequences to both technical and non-technical audiences.

Nice To Haves

• Experience with geographic or geodemographic data systems.
• Familiarity with data collaboration or data marketplace business models.
• Exposure to enterprise security assessment processes (SOC II, ISO 27001 questionnaires, vendor due diligence).
• Experience with broadcast or CTV campaign workflows and measurement.

Responsibilities

• Own the product backlog: write, refine and prioritize epics, features, and user stories with technically rigorous acceptance criteria that engineering can build against.
• Use AI tools – including large language models and agentic assistants – to accelerate specification writing, research synthesis, documentation and analytical tasks, treating them as core productivity infrastructure, not novelty.
• Drive features through the full development cycle – from detailed specification through sprint execution, QA and release – ensuring on-time, on-spec delivery.
• Run day-to-day Agile ceremonies (Sprint Planning, Stand-ups, Backlog Grooming, Retrospectives) and remove blockers that slow the team down.
• Manage bug triage and technical debt priorities, making clear trade-off recommendations to the VP based on data and delivery impact.
• Define and monitor product and platform metrics (match rates, latency, throughput, error rates) to catch issues early and validate that shipped features perform as expected.
• Write detailed technical specifications, data flow diagrams and API contracts for platform components including segment resolvers, delivery gateways, identity stream processors and clean room integrations.
• Work alongside an engineering team that uses agentic coding tools as part of their standard workflow; understand how AI-assisted development affects scope estimation, code review and delivery velocity.
• Work shoulder-to-shoulder with developers on system design, reviewing pull requests and architecture decisions to ensure alignment with product intent.
• Coordinate engineering work across cloud infrastructure (Azure, Snowflake), identity resolution systems (RampID, UID2.0, HEM, MAID) and third-party partner integrations (LiveRamp, DSP/SSP ad platforms).
• Participate in technical design reviews and contribute to architecture decision records.
• Validate integration behaviour through hands-on testing and acceptance of delivered features.
• Apply working knowledge of the Canadian media and advertising ecosystem – including broadcast/linear TV, CTV/OTT, programmatic display/video and retail media – to inform product requirements and partner conversations.
• Support the development of audience activation workflows that connect EA’s geodemographic data (PRIZM segments, DemoStats, SocialValues) to media buying and campaign measurement use cases.
• Work with media agency and broadcast partners to understand their technical workflows, data formats and integration requirements.
• Translate campaign effectiveness and attribution concepts into concrete product features and data deliverables.
• Stay current with shifts in media buying infrastructure: identity deprecation, attention metrics, consent frameworks and measurement methodologies (including cross-media measurement).
• Ensure all product specifications comply with Canadian privacy legislation (PIPEDA, Quebec Law 25/Bill 64) and emerging federal frameworks (CPPA), with particular attention to consent management, data minimization and breach notification requirements.
• Translate regulatory and vendor compliance requirements into concrete engineering constraints and acceptance criteria.
• Evaluate third-party vendor infrastructure (identity graphs, clean rooms, CMPs) against Canadian data residency, consent and cross-border transfer requirements.
• Track privacy-impacting platform changes from major ecosystem players (Google Consent Mode, Apple ATT) and flag product implications to the VP.
• Partner with sales to build technically grounded use cases, product demonstrations and enablement materials for enterprise clients.
• Create and maintain product documentation: technical specifications, integration guides, API references and training materials.
• Coordinate with technology partners (LiveRamp, DSPs/SSPs) on integration timelines, testing and issue resolution.
• Gather and synthesize client and partner feedback into actionable backlog items, escalating strategic themes to the VP.

Benefits

• We celebrate diversity and are committed to creating an inclusive environment for all employees.
• Please note the request in your application if you require any accommodation to participate in the hiring process.
• We welcome people of all abilities.
• At EA, you will solve meaningful and challenging tasks with a friendly team of the most brilliant minds.
• We hire personality, not just a pair of hands.
• Here, you’re free to express your unique qualities, explore different domains and technologies that interest you.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level