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Rippling

Manager, Growth Engineering Revenue Operations San Francisco, CA

Rippling, San Francisco, California, United States, 94199


Rippling gives businesses one place to run HR, IT, and Finance. It brings together all of the workforce systems that are normally scattered across a company, like payroll, expenses, benefits, and computers. For the first time ever, you can manage and automate every part of the employee lifecycle in a single system.Take onboarding, for example. With Rippling, you can hire a new employee anywhere in the world and set up their payroll, corporate card, computer, benefits, and even third-party apps like Slack and Microsoft 365—all within 90 seconds.Based in San Francisco, CA, Rippling has raised $1.2B from the world’s top investors—including Kleiner Perkins, Founders Fund, Sequoia, Greenoaks, and Bedrock—and was named one of America's best startup employers by Forbes.We prioritize candidate safety. Please be aware that all official communication will only be sent from @Rippling.com addresses.About the role

The Growth Engineering team is dedicated to building best in class products, data infrastructure, and processes designed to give marketers the ultimate leverage for campaign execution. The team partners very closely with Go-To-Market and data teams, in a collaborative relationship, to build solutions that amplify the effectiveness of the Rippling GTM strategy – everything from ML recommendation algorithms, to core data infrastructure / pipeline work, to building marketing products and complex workflows, to proprietary data funnels, and much more.We are seeking a strategic and business minded individual to lead a team of innovative software engineers dedicated to applying marketing principles with engineering methodologies to create models, algorithms, and systems that improve marketing strategies and outcomes.What you will do

Develop and execute data-driven growth strategies aligned with business goals.Collaborate cross-functionally with key marketing, product, ops, sales, and data stakeholders.Manage our marketing / growth data infrastructure and build a true internal CDP.Build scalable internal growth products to disrupt 3rd party technology limitations.Implement engineering processes / workflows to handle complex algorithmic jobs.Collaborate closely with product management, sales and marketing teams to understand business needs, growth objectives, and market dynamics.Champion a culture of innovation and technical excellence, encouraging experimentation and exploring new opportunities for business growth.Drive continuous improvement in engineering processes, tools, and methodologies to enhance efficiency and quality.Provide strong leadership to the engineering team, fostering a culture of collaboration, innovation, and continuous improvement.Set clear goals, expectations, and performance metrics for the engineering team, holding individuals accountable for their deliverables.What you will need

A minimum of 3 years managing high performing engineering teams.Bachelor's or Master's degree in Computer Science, Engineering, or a related field.Proven track record of success in leading and scaling engineering teams in a fast-paced, high-growth environment.Strong business acumen and ability to translate business objectives into technical strategies and execution plans.Excellent interpersonal and communication skills, with the ability to collaborate effectively with diverse stakeholders.Demonstrated experience in building and maintaining strong relationships with sales, marketing, and other cross-functional teams.Solid understanding of software development lifecycles, agile methodologies, and modern engineering practices.Strong analytical and problem-solving abilities, with a focus on data-driven decision-making.Ability to manage multiple projects and priorities simultaneously, ensuring timely delivery of high-quality results.Additional Information

This role will receive a competitive salary + benefits + equity.The pay range for this role is: 162,000 - 283,500 USD per year (US San Francisco Bay Area).

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