Marketing Data Manager

Are you looking for a highly impactful role?

Then Jobber might be the place for you! We’re looking for a Marketing Data Manager to join the Demand Generation team.

Jobber exists to help people in small businesses be successful. We work with small home service businesses, like your local plumbers, painters, and landscapers, to transform the way service is delivered through technology. With Jobber they can quote, schedule, invoice, and collect payments from their customers, while providing an easy and professional customer experience. Running a small business today isn’t like it used to be—the way we consume and deliver service is changing rapidly, technology is evolving, and customers expect more. That’s why we put the power and flexibility in their hands to run their businesses how, where, and when they want!

Our culture of transparency, inclusivity, collaboration, and innovation has been recognized by Great Place to Work, Canada’s Most Admired Corporate Cultures, and more. Jobber has also been named on the Globe and Mail’s Canada’s Top Growing Companies list, and Deloitte Canada’s Technology Fast 50™, Enterprise Fast 15, and Technology Fast 500™ lists. With an Executive team that has over thirty years of industry experience of leading the way, we’ve come a long way from our first customer in 2011—but we’ve just scratched the surface of what we want to accomplish for our customers .

The Team

This role sits on the Demand Generation team and is designed to close a critical gap: attribution is currently a high-impact, high-risk function without dedicated coverage, creating delays, inconsistencies, and a single point of failure.

The Role

We’re looking for a Marketing Data Manager to join Jobber’s Demand Generation team and take dedicated ownership of attribution excellence , where our go-to-market investments (including a significant inbound lead spend) are measured accurately, confidently, and consistently.

The Marketing Data Manager will be the primary owner of marketing attribution and marketing data enablement, working in close partnership with our data teams on the supporting data infrastructure, while also supporting specialized, applied analytics work across the top of the funnel, including experiment measurement and improving data flows that support outbound and retargeting motions.

Why this role matters

Attribution is a foundational input to how we evaluate ROI and prioritize spend. When attribution is broken, delayed, or inconsistent, it introduces real risk and slows decision-making. This role creates dedicated focus, faster feedback loops, fewer errors, and higher confidence for key stakeholders—while also strengthening continuity and resilience across RevOps.

The Marketing Data Manager will:

Evolve Attribution Modelling & Methodology

Manage and improve our first-touch attribution model, incorporating new signals and partnering with Analytics to align on business definitions, methodology, and interpretation.

Enhance our multi-touch attribution model, including bringing in non-clickable sources such as connected TV and Salesforce data, in partnership with Analytics on methodology and interpretation.

Build model comparison analyses and reporting to evaluate newly developed models against existing first-touch and multi-touch approaches.

Act as the primary point of contact for diagnosing attribution inconsistencies, partnering with Marketing and Customer Analytics stakeholders to understand perceived under-performance and uncover root causes in data and configuration.

Data Integration & Attribution Infrastructure

Integrate new marketing attribution sources end-to-end, including partnering with our data teams to develop reverse ETL models and seed tables needed to sync data into the attribution systems

Maintain and update attribution seed tables (e.g., adding influencers/partners and implementing UTM mapping changes). Partner with BI to review published PRs and confirm changes meet standards for accuracy, integrity, and alignment with attribution logic.

Monitor and validate UTM structures and attribution signals, proactively identifying mapping issues and irregularities that impact reporting accuracy.

Coordinate with Ad Operations to ensure tracking configurations align with attribution needs and that collected web data is structured and usable for modelling.

Data Modelling

Write and maintain production-quality SQL to analyze raw marketing, product, and revenue signals into analysis-ready and reverse ETL datasets.

Translate data analysis into dimensional/semantic model requirements (e.g., clean attribution-ready tables, standardized channel mappings, and reusable metrics definitions) that downstream reporting and stakeholders can trust.

Collaborate with the relevant data teams to review and maintain data models that support first-touch and multi-touch attribution, including new source onboarding, table improvements, and model comparison reporting.

Review and maintain quality checks and validation logic to ensure changes to data models, UTMs, and attribution logic don’t break downstream reporting.

Partner with BI and stakeholders to align on definitions, logic, and documentation, ensuring datasets are understood, governed, and reusable across the org

Documentation, Training & Stakeholder Enablement

Lead attribution onboarding/training for new Marketing hires, including how account-level attribution is derived and interpreted

Develop and maintain documentation for:

Attribution logic and frameworks

Seed table dictionaries

UTM standards

Model configuration

Support Applied Top-of-Funnel Analytics & Growth Operations

Support proactive enhancements that improve attribution ROI and stakeholder confidence.

Help operationalize prospect data flows (e.g., cleaning/loading cold prospect data into tools used for retargeting, sequencing, and warming), so GTM teams can execute reliably

To be successful, you should have:

Strong experience in attribution, marketing analytics, or revenue analytics in a high-velocity GTM environment.

The ability to own ambiguous, high-stakes measurement problems end-to-end, from data inputs to stakeholder-ready outputs.

Proven skill in diagnosing complex inconsistencies across tracking, data pipelines, and business logic.

Comfort partnering cross-functionally (RevOps, Marketing, BI, Ad Ops) and translating technical work into clear, practical guidance.

A builder mindset: you document, enable, and improve systems so the organization scales beyond you.

Strong SQL skills - comfortable writing and maintaining complex queries independently to investigate data issues, not just interpreting dashboards or requesting analysis from others.

Data modelling experience has built or maintained clean, reusable datasets and table structures (e.g., standardized metric definitions, dimensional models) that other teams and reporting can reliably build on top of.

Comfort working directly in the data layer - you have partnered with or worked alongside data/analytics engineering teams on schema design, ETL processes, or pipeline logic, even if not the primary owner of that infrastructure.

Location:

We believe great collaboration is intentional, and sometimes that means coming together in person to build, brainstorm, and connect. To support this, the role is open to candidates based in one of our hub cities: Edmonton, Toronto, Vancouver, or Kitchener-Waterloo.

Compensation:

At Jobber, we believe that compensation should be transparent, fair, and reflective of your experience and growth. This role has a minimum annual salary of $98,300 a midpoint of $115,700, and a maximum salary of $133,100, designed to show the progression from learning the ropes to truly excelling.

We design our compensation to reflect each new hire’s skills, experience against the complexity of the role, ensuring a fair and competitive salary. Our range is intentionall