Mark Jewett has spent most of his career standing between a complicated machine and a room full of people wondering what, precisely, it will do for them. The machine has changed names every few years. First it was the enterprise application, then the database, then the cloud, then visual analytics, then artificial intelligence. The room has changed too. Developers gave way to IT leaders, analysts, executives, and now life-sciences teams. Jewett's role has remained strikingly stable: learn the machinery well enough to explain why it matters.
That task sounds modest until one considers the material. SQL Server, Azure Stack, Tableau, enterprise data management, and healthcare intelligence are not products that sell themselves in a sentence. Each arrives with its own grammar, technical dependencies, organizational anxieties, and promises about a future that is always arriving slightly ahead of schedule. Jewett, a Seattle-based executive who describes himself as a “data geek at heart,” has built a 25-year career out of removing just enough fog.
In October 2025, he became Chief Marketing Officer of Komodo Health. The remit is broad: brand, communications, product marketing, demand generation, and go-to-market execution. The platform he is helping explain, Marmot, applies AI to a vast map of de-identified healthcare journeys so life-sciences organizations can investigate questions and make decisions faster. The vocabulary is new. The underlying assignment is familiar.
A résumé that reads like a history of data
Jewett's path through enterprise software is unusually chronological. At Siebel, he worked in the age of enterprise applications. At Microsoft, where he spent sixteen years, he moved through SQL Server, big data, data-center infrastructure, and cloud computing. He later spent five years as senior director of Azure Hybrid Cloud Marketing. When he joined Tableau in January 2018 as vice president of product marketing, the center of gravity had moved again: data was no longer merely stored or managed. It had to be seen, explored, and discussed by people across the business.
There is a revealing detail from his arrival at Tableau. Elissa Fink, then the company's chief marketing officer, said Jewett did not wait a week before he was already demoing the products. It is the sort of detail that separates product marketing from the ornamental arts. To translate a system, one must first touch it, stumble through it, and understand where the customer might stumble too.
Tableau was then broadening its subscription business and trying to reach more enterprise buyers, IT departments, and business analysts. Jewett's background in the cloud gave him a useful dialect. Yet his public work there increasingly emphasized people over infrastructure. He talked about “data culture,” which he defined as the collective behaviors and beliefs of people who value, practice, and encourage the use of data to improve decisions. Software could support such a culture. It could not substitute for one.
The customer is usually asking a second question
Years earlier, while marketing Azure Stack, Jewett saw how quickly customer expectations could outrun a product category. Microsoft had imagined that some enterprises would want a limited collection of public-cloud services in their own data centers. Customers asked for more. “How fast can I get full parity with Azure?” was the question he kept hearing. They wanted the cadence of the public cloud, including the next feature and the one after that, within the constraints of an on-premises environment.
The episode has the shape of good market listening. The literal request concerned features. The larger request concerned continuity. Customers wanted to know whether choosing a constrained environment meant accepting a slower future. Jewett's explanation of Azure Stack had to connect architecture, update reliability, security, hardware partnerships, and the customer's appetite for change. The marketer's job was not to make any of those tensions disappear. It was to make them legible.
At Tableau, the same instinct appeared in a different form. Jewett argued that giving teams access to data could create responsibility rather than chaos. “The more trust you put in a team,” he said, “the more accountable they feel to use it responsibly and effectively.” This was not a pitch for access without rules. It was a view of trust as an operating system: give people the tools, expectations, and room to act, and they may become better custodians of the information.
The brief retirement and the return to data
Jewett rose to senior vice president of product and partner marketing at Tableau and left in late 2021, after Salesforce had acquired the company. Then came what one former colleague teasingly called a “temporary retirement.” In January 2024, Jewett returned to an executive role at Informatica as senior vice president of portfolio marketing. His responsibilities covered product, industry, partner, and content marketing, along with competitive intelligence. It was not a small portfolio. His announcement sounded less like a return from the wilderness than a data enthusiast discovering another large set of shelves.
His reason was direct: Informatica sat at the intersection of data, AI, and cloud. The company had moved its products toward the cloud and integrated AI more deeply. Jewett saw a familiar organizational drama: an established company choosing to disrupt its own habits before someone else did it for them. He also saw the marketer's leverage. A strong portfolio team could focus the company on the best opportunities, sharpen how it reached customers, and turn technical transformation into commercial momentum.
His writing at Informatica returned to a theme that had followed him from Microsoft and Tableau: trust arrives before scale. Excitement about generative AI was plentiful, he observed, while many organizations still struggled to move pilots into production. The problem often began beneath the model. Useful AI required data that was complete, accurate, reliable, governed, and secure. It was a decidedly unglamorous point in a glamorous season, which is precisely why it mattered.
Komodo makes the stakes concrete
Komodo Health brought the arc of Jewett's career into a more specialized arena. Its platform is designed for questions across clinical development, market access, commercialization, and real-world evidence. The customers do not merely need an attractive output. They need to understand where an answer came from, whether it can be reproduced, and how confidently it can support a consequential decision. This is data culture wearing a lab coat, with less tolerance for hand-waving.
Jewett joined at the moment Komodo was scaling Marmot, its AI platform. He wrote that three things drew him: the mission, the people, and the chance to build. By mid-2026, his public updates focused on enterprise adoption, including an expanded partnership with Alnylam and demonstrations of how reporting cycles could move from months to hours. He also highlighted the harder side of AI trust: explainability, reproducibility, governance, verification, and compliance. The old product-marketing problem had acquired sharper consequences. An answer could be quick, fluent, and still require proof.
What Jewett brings to that problem is not healthcare celebrity or scientific authorship. It is the accumulated memory of how enterprise technologies earn a place inside cautious organizations. Databases had to become dependable. Cloud services had to respect real-world constraints. Analytics had to escape the specialist's desk without abandoning governance. AI now faces all of those adoption tests at once.
The career outside the product launch
A public résumé can turn a person into a tidy stack of logos. Jewett's volunteer work complicates the picture in a useful way. Since 2021, he has served as board secretary and a volunteer reader for College Guild, which provides free correspondence courses to incarcerated people. His profile also lists long-running support for the ACLU, Sierra Club, University District Food Bank, and Doctors Without Borders USA. Those commitments are not marketing case studies. They do, however, echo his professional interest in access, learning, and what happens when information moves between people.
An older family blog from a period in Singapore offers another small aperture. Jewett wrote with evident pride when his wife returned to full-time teaching after more than a decade centered on raising their children. He paid attention to the invisible work behind the milestone: keeping credentials current, teaching part time, preserving a professional identity. It is a warmer kind of operational detail, far from a keynote stage.
The most persuasive portrait, then, is not of a marketer sprinkling charm over complex software. It is of an operator who likes the complexity enough to enter it, then respects the audience enough to come back with a clearer sentence. That instinct has survived several corporate chapters and almost every fashionable noun in enterprise technology.
At Komodo, Jewett says the right combination of technology and storytelling can accelerate adoption. The order is important. The technology must work. The story must reveal rather than disguise it. Somewhere between those obligations sits the durable craft of his career, still translating.