Marketing Analytics Manager

We are hiring a Marketing Analytics Manager to own the layer between our marketing data and the decisions our team makes - providing reliable analytics, translating insights into clear stories, and making the whole team sharper because of it. Twist Bioscience's marketing team runs a sophisticated B2B and e-commerce funnel across Salesforce, Snowflake, and Tableau, with Segment for event tracking and a migration to Salesforce Marketing Cloud under way. Our central Business Intelligence (BI) team owns the data platform - pipelines, uptime, core fact tables - and marketing operates as a customer of that layer. This Marketing Analytics role will own the translation layer between BI's data and the decisions the business makes. You will be the steward of marketing's own data product layer: a governed Snowflake database that already feeds lead scoring, Data Cloud, and cross-functional reporting. You'll own the data model, the metric definitions, and the delivery of insight - both through self-serve endpoints for leaders who want to query the data themselves, and through curated narratives and dashboards for those who want trusted answers in a fixed format or cadence. There's a solid data foundation in place and a team that's actively invested in analytics. What this role adds is the person who formalizes and builds on it: completing campaign performance reporting and driving its wide adoption, supporting a migration from Marketo to Salesforce Marketing Cloud, and putting structure around things the team needs - a documented data model, a metric dictionary, automated quality checks. There's a lot of room to shape how marketing analytics works here, and the team is ready for someone to jump in and drive. What you'll do - Own the data model and metric definitions. Document and maintain a single, authoritative marketing data model - funnel stages, what an MQL actually is, how campaign attribution works. Every dashboard, every report, every executive readout is grounded on it. When two dashboards show seemingly different numbers for the same metric, your job is to diagnose and either educate the team on the interpretation, or fix the underlying data model fast. - Deliver marketing measurement end to end. Marketing performance across the funnel, delivered as compelling stories grounded in the business, and that come with recommendations - not just numbers. You lead with the conclusion, calibrate the depth to your audience, and own the "so what.

" - Work the business problem with stakeholders. Commercial marketing, product marketing and digital marketing leaders are your primary customers. You work alongside them on why a channel is underperforming, where the funnel leaks, which segments to lean into. You bring problem-statement discipline: they describe the symptom from where it affects them, you determine the root cause. - Own lead quality measurement. MQL definition and lifecycle metrics, lead scoring validation, and the analysis that tells us whether marketing is delivering a pipeline that closes. - Build two distinct delivery channels. Self-serve: publish clear, documented endpoints and datasets so leaders who want to query the data themselves can do it accurately. Full-serve: curated visuals, recurring digests, and narrative summaries for stakeholders who want trusted, actionable answers on a fixed cadence. - Be the quality layer. Sanity-check self-served numbers before they reach a decision. Set up automated validation checks so interpretation or reporting problems surface fast, not after someone puts a bad number on a slide. - Build AI-assisted analytics tools. Maintain Marketing’s semantic layer and metric dictionary to ensure both Tableau dashboards and AI-assisted self-serve interfaces deliver standardized answers - Steward the marketing data product layer. Marketing owns a governed Snowflake database that feeds lead scoring, Data Cloud, and downstream reporting.