Senior Marketing Insights Analyst

Paddle•Toronto, ON

1d•CA$110,775 - CA$144,299•Hybrid

About The Position

Paddle offers digital product companies a completely different approach to their payment infrastructure. Instead of assembling and maintaining a complex stack of payments-related apps and services, we're a Merchant of Record for our customers. That means we take away 100% of the pain of fragmentation. It's faster, safer, cheaper, and, above all, way better. We're backed by investors including KKR, FTV Capital, Kindred, Notion, and 83North and serve over 6,000 software sellers in 245 territories globally. We're looking for a Senior Marketing Insights Analyst to sit at the heart of our Marketing team and report into the Marketing Ops & Programs Lead. You'll be the analytical engine behind our marketing investments: turning data across sources into clear opportunity and performance narratives, actionable insights, and recommendations that steer how we invest and optimise. This is not a back-office data role. You'll be embedded in Marketing Operations, working closely with channel owners, campaign managers, and marketing leadership to make sure every program and campaign we run is measured well and iterated on quickly. You'll also partner closely with our Senior Marketing Analytics Engineer in Data Engineering, ensuring our upstream data infrastructure is world class.

Requirements

8+ years of experience in marketing analytics, marketing operations, or a closely related role, ideally within a B2B SaaS environment where you have owned a measurement or attribution strategy, not just executed within one.
Hands-on experience with a B2B attribution platform (such as Deamdata), a CRM and marketing automation stack (such as HubSpot and Salesforce), and BI tooling (such as Omni, Looker, or Tableau).
Solid SQL skills: you can join, aggregate, and sanity-check data across warehouse tables yourself, and you can read a dbt model well enough to challenge it.
Deep judgment on marketing measurement: you know the strengths and limits of multi-touch attribution, when to reach for incrementality testing or experiments instead, and how to explain the difference to a non-analyst.
The ability to translate complex data into plain-language recommendations, not just presenting what happened, but advising what to do next.
Strong stakeholder management: you're comfortable presenting to a CMO and a paid media specialist on the same day and calibrating your message accordingly.

Responsibilities

Own the marketing performance narrative: define questions that matter, and deliver decision-ready insights to channel owners and marketing leadership on a regular cadence, from weekly channel reviews to quarterly business reviews.
Shape how marketing budget is allocated: build the forecasting, scenario modelling, and benchmarking that informs quarterly and annual planning, and make clear recommendations on where to invest, hold, or pull back.
Own our revenue attribution practice: maintain and evolve our attribution models, interpret multi-touch and pipeline contribution data, and be the team's authority on what is genuinely driving pipeline and revenue.
Design and run incrementally tests to validate what attribution alone cannot tell us, and build the team's understanding of when to trust each method.
Define measurement frameworks with channel owners (paid media, social, web, SEO & AEO, content) before campaigns launch: agree success metrics, targets, and test designs up front, not retrospectively.
Analyse the full buyer journey across HubSpot and Salesforce: surface funnel trends, conversion bottlenecks, and anomalies from lead creation through lifecycle progression to opportunity and closed-won.
Lead campaign and program post-mortems: quantify what worked and what didn't, and turn findings into specific changes to targeting, spend, or creative for the next cycle.
Set requirements for our GTM data layer: define what marketing needs from Snowflake and dbt models, write acceptance criteria, and partner with our Senior Marketing Analytics Engineer who owns implementation.
Extend measurement beyond the funnel: contribute to how we track brand and upper-funnel signals such as branded search, share of voice, and awareness, so investment cases for brand spend rest on evidence.
Raise the analytical bar across the team: coach channel owners on interpreting their own dashboards, standardise definitions, and reduce ad hoc reporting requests by making self-serve genuinely work.