Growth Marketing Manager, Performance Marketing
Maven ClinicFull Time
Mid-level (3 to 4 years), Senior (5 to 8 years)
Candidates should have 4-5 years of experience in performance marketing, demand generation, growth marketing, or digital marketing. Deep expertise in B2B paid channels such as Google Ads, LinkedIn Campaigns Manager, and Facebook Ads is required. Proven ability to create strategic briefs and work cross-functionally with various teams is necessary, along with strong project management skills. Experience partnering with Marketing Operations and using automation platforms like Hubspot is expected. Familiarity with Google Analytics, 6sense, and Salesforce is a plus, as are advanced analytical skills and comfort with reporting platforms. Startup or high-growth experience is also a strong plus.
The Growth Marketing Manager will own the development, execution, and optimization of digital marketing programs across paid, email, webinars, and organic channels to drive measurable impact. They will support enterprise and strategic segment campaign creation and optimization across Google Ads, LinkedIn Campaigns, Facebook Ads, and Influ2. Responsibilities include partnering with content on keyword strategies for paid search, supporting owned channel conversion initiatives, managing email marketing requests, and collaborating with marketing operations for campaign setup and performance tracking. The role involves measuring and reporting on campaign results, sharing insights, identifying opportunities, and experimenting with innovative tactics to unlock new growth opportunities.
Provides end-to-end data observability solutions
Monte Carlo Data helps businesses ensure the reliability of their data through end-to-end data observability, allowing real-time monitoring of data freshness, volume, schema, and quality. Their platform includes tools for incident detection and resolution, which assist analysts in addressing data quality issues efficiently. By integrating with communication tools like Slack and JIRA, it fits seamlessly into existing data management processes. The goal is to help businesses avoid the costs associated with bad data, making it suitable for data-dependent companies across various industries.