The board
Benchling · Marketing- Pay
- $50 – $60 per hour
- Where
- San Francisco, CA
- Posted
- Aug 3
This is a 6 month contract in-office role with a required hybrid schedule — a minimum of three days per week (Monday, Tuesday, and Thursday) at our San Francisco HQ.
Our marketing data layer was built incrementally over several years, and it shows. The models, dashboards, and pipelines powering our funnel reporting, campaign attribution, and SDR workflows have accumulated patches and gaps that are increasingly holding us back particularly as we push into AI-driven marketing tooling that requires clean, well-documented data to work reliably.
We're looking for a mid-level marketing data analyst for a focused 6-month engagement embedded with the Marketing Operations team.
What you'd do
- Own the dbt + Sigma layer for the marketing funnel, from campaign member to MQL/MSL, meeting and opportunities. Resolve dependencies, filling model gaps, and documenting logic end-to-end.
- Integrate new data sources into Snowflake: ad platform spend (Google, LinkedIn), GA4 traffic and conversion data, and Gong conversation and meeting object.
- Build and update marketing dashboards: funnel stage conversion, pipeline generation (effort, health, velocity), SDR activity and MQL outcomes, and per-product ARR attribution. Integrating new data sources into them.
- Build quality control and system health monitoring across the marketing stack: Marketo to SFDC sync health, lead routing coverage, data freshness, and email deliverability signals.
- Partner with our internal data team and other GTM analysts to align on core GTM data models.
- Produce a data dictionary: plain-language definitions of key marketing concepts and data model semantics written for both team and LLM consumption.
What they want
- 4+ years in marketing analytics or marketing operations at a B2B SaaS company.
- Strong SQL skills and hands-on experience with dbt for data modeling and github for version control.
- Experience with Snowflake and a modern BI tool. Sigma strongly preferred.
- Working knowledge of Salesforce and Marketo data structures; you understand what an MQL is and how it moves between systems.
- Familiarity with marketing attribution concepts: campaign member models, multi-touch attribution, and lead-to-opportunity conversion.
- Experience building and documenting data models for non-technical consumers.
- Self-directed and comfortable working as an embedded contractor on a defined-scope engagement.