PadSplit is hiring a MarTech Analyst to own the measurement infrastructure that powers lifecycle marketing for Member and Host Growth to report into our Director of Performance Marketing. This means full ownership of our Customer Data Platform (Segment), our attribution stack (Rockerbox), and the event taxonomy that connects every marketing dollar and effort to member and host outcomes. You'll also serve as the technical bridge between our lifecycle automation platform (Iterable and Pardot) and Salesforce + analytics layer — ensuring that what we send, and when, is informed by clean, trustworthy data.
This is an ownership role, not a ticket-taker role. You will sit at the intersection of marketing, data engineering, and product analytics. If you find joy in diagnosing why two dashboards don't agree, building event schemas that scale across mobile and web, and using AI to eliminate the manual work that slows decisions down — this role was designed for you. You cannot only report on what happened, but can also leverage the data to tell the story and what should be done next.
The ideal candidate is a technical builder who has lived inside a CDP and come out the other side with strong opinions about how event data should flow. You have hands-on experience with marketing attribution platforms and know how to interrogate channel performance data rather than just report on it. You are fluent in SQL, comfortable in Python, and you've already incorporated AI tools — LLMs, prompt workflows, or automation pipelines — into your day-to-day work.
You thrive with ownership and ambiguity. You work async in English with confidence. You are the person your last team called when the numbers didn't add up, and you liked that call. You understand that measurement infrastructure does not support work — it is the foundation on which every growth decision is made.
- Own Segment CDP governance: Maintain and evolve the event taxonomy across web, mobile, and server-side sources. Own cross domain and cross identity mapping. Audit data quality, resolve identity resolution issues, and ensure every marketing tool downstream receives clean, reliable data.
- Own Rockerbox attribution: Serve as the day-to-day owner of our multi-touch attribution platform. Diagnose channel-level performance, investigate attribution anomalies (including consent tool impacts), and build the feedback loops that inform paid media spend decisions.
- Build and maintain marketing measurement infrastructure: Develop and document the measurement layer for all Member and Host Growth experiments — owning success metrics integrity, building pre/post cohorts, and ensuring statistical validity before results are acted upon acting as a consultative partner to marketing.
- Support lifecycle automation analytics: Partner with our Marketing Automation team (Iterable) to ensure behavioral triggers, segmentation logic, and campaign performance data are accurate and actionable. Audit automation flows for data integrity.
- Build AI-augmented marketing analytics workflows: Identify repetitive analysis tasks — weekly reporting, anomaly detection, data quality checks — and replace them with AI-powered pipelines. You will be expected to actively prototype and ship AI workflows, not just evaluate them.
- Partner across data, product, and paid media: Collaborate with our Data team (Snowflake warehouse), Performance Marketing (Rockerbox, AppsFlyer, Google/Meta), and Product (Segment instrumentation on new features) to ensure the measurement layer scales as the business does.
- Build and maintain marketing dashboards: Own the marketing measurement layer in Hex and other BI tools. Create dashboards that give the team a single source of truth on CAC, conversion velocity, funnel efficiency, and channel-level attribution.
- Diagnose attribution and data quality issues: When a metric looks wrong, you investigate and resolve it — not escalate it. You own the answer.
- Segment CDP mastery: Deep, hands-on experience managing a Segment workspace — event schemas, sources, destinations, identity resolution, and data governance. You know what a track call should look like and why it matters.
- Attribution platform experience: Hands-on experience with Rockerbox, AppsFlyer, or a comparable MTA platform. You understand first-touch vs. last-touch vs. data-driven attribution and know when each is the right lens.
- Optimizing Cross-Platform Integrations experience: You know how to make systems talk to one another leveraging tools like Zapier or Make to connect marketing, CRMs (Salesforce + ZenDesk), attribution tools and reporting systems. You love good automation.
- SQL proficiency (required): You write complex analytical queries independently — CTEs, window functions, cohort logic. Snowflake or BigQuery experience preferred.
- Python proficiency (strongly preferred): Experience using Python for data manipulation, pipeline scripting, or analysis automation. Pandas, dbt, or similar tooling is a plus.
- AI/LLM hands-on experience: You have built something with an LLM — a prompt-based workflow, an automated analysis pipeline, an agent-assisted reporting tool, or similar. You approach AI as a productivity multiplier, not a novelty.
- Lifecycle/ESP/CRM analytics experience: Familiarity with Iterable, Braze, or a comparable lifecycle platform — specifically the analytics and data layer, not just campaign execution.
- Marketing analytics fluency: You understand CAC, LTV, conversion rate by funnel stage, channel specific nuances and ROAS. You can move between a data model and a marketing strategy conversation without losing context.
- English fluency (required): You will work daily with a US-based team. Strong written and spoken English is essential for async collaboration, documentation, and cross-functional alignment.
- Experiment measurement: Experience designing measurement frameworks for A/B tests — control/treatment cohort construction, metric selection, and results interpretation.
- Your application will be reviewed for possible next steps by the Hiring Manager.
- If you meet eligibility requirements, the next step would be a phone screen with a member of the PeopleOps team for approximately thirty (30) minutes.
- If warranted, the next step would be a video interview with the Director of Performance Marketing for forty-five (45) minutes.
- If warranted, the next step would be a technical assessment and video interview with a small panel of key stakeholders (Data, Performance Marketing, Marketing Automation) for one (1) hour. Candidates will walk through a live data scenario for discussion.
- If warranted, the final step would be a thirty (30) minute interview with the VP of Member Growth and the President.
- If warranted, then we move to offer!
Compensation is based on the role's scope, national market benchmarks, the person's expertise and experience, and the impact of their contributions to our business goals.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
