Field Marketing Manager, Mexico
Databricks Mosaic · Mexico City
CHECKED 15H AGO
Infrastructureonsitesenior
At a glance
Highlights
- Own field marketing engine for one of Databricks' fastest-growing LATAM markets.
- Turn customer insights and global programs into local full-funnel demand.
- Use attribution data to scale repeatable motions that accelerate sales success.
What they offer
- Comprehensive health coverage including medical, dental, and vision
- 401(k) Plan
- Equity awards
- Flexible time off
- Paid parental leave
- Family Planning
- Gym reimbursement
- Annual personal development fund
- Work headphones reimbursement
- Employee Assistance Program (EAP)
- Business travel accident insurance
Ideal candidate
Data-driven B2B marketer who thrives partnering with sales to drive pipeline. You love turning insights into full-funnel programs and optimizing for ROI in fast-growing SaaS markets.
Requirements
- 6+ years of B2B marketing experience, including 2-4 years in field marketing with pipeline and revenue accountability
- Proven success building marketing-sourced pipeline with direct sales and SDR/XDR teams, ideally in high-growth or SaaS
- Hands-on experience designing integrated full-funnel programs across events, digital, account-based and partner activities
- Strong marketing operations aptitude with Salesforce and marketing automation for campaigns, leads and attribution
- Demonstrated ability to use data and experimentation for investment decisions, conversion analysis and ROI optimization
- Experience partnering with sales leaders to co-build territory and account plans into marketing strategies and plays
- Excellent stakeholder management and communication skills in a matrixed environment
- Willingness to travel for customer meetings and programs within Mexico and occasionally across the Americas
Lab profile
About Databricks Mosaic
Builds unified data analytics and AI platform to productionize AI applications.
What they build
- Databricks platform
- Unified Data Analytics and AI
- AI platform
Known for
- Forward-deployed AI engineering
- Productionizing first-of-kind AI applications
- Customer platform adoption and scale
- Cross-functional engineering and product collaboration