From $1M to $3B ARR: Databricks CRO Ron Gabrisko on Scaling a Revenue Rocket Ship

In the latest episode of SaaStr’s CRO Confidential Series, our host Sam Blond sits down with Ron Gabrisko, CRO of Databricks, to unpack the journey from $1M in ARR to crossing $3B ARR at the end of January 2025. With Databricks now one of the largest pre-IPO technology companies, with $10 billion of expected non-dilutive financing and a valuation of $62 billion, Ron’s insights are gold for any revenue leader looking to scale.

Hiring for Domain Expertise in a Technical Sales Role

While contrarian to Sam’s usual advice to founders and revenue leaders not to over-index on domain experience as it often leads to trade off for other attributes in a sales candidate,  Sam kicks off the conversation by admitting that a technical sale to a technical buyer might be its own unique category where domain experience is something you would want to solve for. For context, Ron has an MBA and a master’s in engineering from Stanford. His view is your sales team teaches your customers how to get value out of your product. So if you’re not technical enough to understand the product and understand how it works, it’s hard to teach your customers. (You gotta know the product cold.)

Ron explains: “We  hire mostly technical backgrounds, but as our customers get larger and larger, you start to get global account managers, and they’re going to have much more business strategic account management experience. Similar to most structures of a technical sales team.

We have account executives, solution architects, SDRs, and specialists, and every function in the mix of those functions. We tend to be very technical. A lot of them can code, they can do POCs, they can do pilots. They’re not just doing demos. And we expect our salespeople to understand the technology. So we have a mix of both, but I think as we’ve scaled it’s become an advantage. From the early days, we had a more technical sales team.”

The Early Days: Finding the First Customers

Databricks started with a unique advantage: Spark, the open-source project developed by its founders, was already widely adopted. The challenge was figuring out how to monetize that adoption.

Step one? Talk to users. “We went to the open-source community and asked, ‘What would you pay for?’” Ron recalls. These early conversations helped shape Databricks’ product, pricing, and go-to-market strategy.

For startups looking to land their first big customers, Ron’s advice is simple:

• Leverage existing user communities.

• Solve for the highest-value pain points.

• Hire early sales reps who are excellent at discovery and customer education.

The Power of Open Source in Sales

One of Databricks’ biggest accelerators was its open-source DNA. “Our founders focused on adoption first, not revenue,” Ron explains. This community-first approach created a massive top-of-funnel for Databricks, which then converted those users into paying customers.

The takeaway? If you have an open-source or freemium model, think beyond just free usage. Build a clear path to monetization by identifying what your power users need most—and charge for it.

Leveraging Investors for Growth

Another underutilized growth channel? Investors. Ron and his team tapped into their VC network, particularly a16z, to land early enterprise deals. “They set up meetings with Fortune 500 CIOs.  I think the VCs have amazing connections for their portfolio companies. And we found a lot of our big enterprise customers through that channel early days.”

A common mistake founders make? Sending generic requests like, “Do you know any CIOs?” Instead, make it easy for investors to help by sending pointed asks like, “Can you introduce me to [specific company’s CIO]? Here’s a blurb you can forward.”

Building the Right Sales Motion

In Databricks’ early days, the sales team was largely inside sales, selling to tech startups in Silicon Valley. But Ron quickly saw that bigger dollars were in the enterprise. Within his first quarter, he hired 40 enterprise reps and built a field sales team targeting financial services and Fortune 500s.

The takeaway? Structure your sales team based on where your biggest revenue opportunities lie. Inside sales can work well for smaller, fast-moving deals. Enterprise sales require a field presence, strategic account management, and a drive to go where your customers are.

Pricing: Keep It Simple (At First)

Databricks started with a simple, consumption-based pricing model. Why? Because that’s how their customers—who were used to AWS, Azure, and GCP pricing—expected to buy.

Ron explains: “For us the more data you have and the more queries and the more analysis and analytics you can do, and the more value you’re going to get out of the product. So having a consumption-based pricing model makes a ton of sense.

And our baseline continues to grow. So as people get more and more data and more and more queries, our revenue grows as well, which I think is a way superior model to a licensing or a seat-based model since eventually you might run out of users. For us data consumption continues to grow.”

The lesson? Price your product in a way that aligns with how customers already budget for similar solutions. Then refine your packaging strategy as you scale.

Turning Customers into Champions

A huge part of Databricks’ growth came from community-driven sales. The company built an army of customer champions by:

• Hosting a yearly customer conference

• Hosting industry roundtables and meetups.

• Creating a Product Advisory Board where top customers helped shape the roadmap.

• Encouraging customers to share success stories at events.

Ron’s advice: “Your best sales tool is a happy customer talking to a prospect.” Create environments—whether through events, forums, or Slack communities—where customers sell for you.

Final Advice for Revenue Leaders

After nearly a decade of scaling Databricks, Ron has one core piece of advice for revenue leaders: hire the best people and invest in them.

“Talent beats everything. Culture beats everything. If I could go back, I’d tell myself to invest even more aggressively early on.”

For any startup looking to go from $1M to $100M and beyond, Ron’s playbook is clear:

• Hire technical sales talent if you’re in a technical market.

• Tap into investor networks for warm intros.

• Keep pricing simple and optimize packaging.

• Build a customer community that fuels demand.

• When you see product-market fit, go all in.

The road from $1M to $3B isn’t easy, but as Databricks has proven, with the right team, strategy, and execution, it’s possible to build a category-defining company.