Marketing Data Analyst - Contractor
San Francisco, California, United States
- Pay
- Salary not listed in the saved posting
- Work setup
- Unconfirmed
- Employment
- Unconfirmed
What you’ll work on
Full postingThis 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.
Own the dbt + Sigma layer for the marketing funnel, from campaign member to MQL/MSL, meeting and opportunities.
Build and update marketing dashboards: funnel stage conversion, pipeline generation (effort, health, velocity), SDR activity and MQL outcomes, and per-product ARR attribution.
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.
From the employer’s posting
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.
RESPONSIBILITIES 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.
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.
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.
What you’ll bring
All qualificationsCore experience
- 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.
- 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.
Qualification wording
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.
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.
Tools in this posting
- SQL
- dbt
- Sigma
- Snowflake
Source — Tool mentions in context
- 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.
RESPONSIBILITIES - 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.
- 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.
- 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.
Job description
We are rebuilding biotech for the AI era.
When a breakthrough is delayed, the world waits. Getting a molecule from discovery to patients, or a crop from lab to field, involves thousands of slow, manual, disconnected steps. AI has the potential to change this, compressing decades of R&D work into years. But that only happens when clean, structured scientific data and AI are built into how science gets done.
Benchling is the AI platform for biotech R&D. Scientists use Benchling to design experiments, capture structured data, and run AI agents and models directly in their workflows. Over 200,000 scientists around the world trust Benchling to power their most important work, from academic labs to Sanofi, Moderna, and more than half of the world's top 50 biopharma.
We’re building an AI scientist for our customers. We can’t do that if we haven’t built the muscle ourselves. AI fluency is the foundation we build on; it's core to how we work, and we're committed to helping every new hire integrate it into their day-to-day. As part of our interview process, you'll complete a brief AI-focused exercise or discussion so we can understand how you think about and use AI to drive impact in your role. Feel free to reference any tools, platforms, or workflows you use today.
ROLE OVERVIEW
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. You'll own the sprint to clean up the underlying data models, ship the core dashboards we've been scoping, integrate new data sources, and document everything well enough that the team and our AI tools can self-serve when the engagement ends.
RESPONSIBILITIES
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.
QUALIFICATIONS
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.
Benchling welcomes everyone.
We believe diversity enriches our team so we hire people with a wide range of identities, backgrounds, and experiences.
We are an equal opportunity employer. That means we don’t discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We also consider for employment qualified applicants with arrest and conviction records, consistent with applicable federal, state and local law, including but not limited to the San Francisco Fair Chance Ordinance.
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
San Francisco, California, United States
ROLE OVERVIEW 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.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
- Status in our records
- Active
- First seen by us
- Aug 3, 2026
- Recorded sightings
- 66
- Last seen by us
- Oct 8, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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