On Formative Experiences

I’m originally from Newark, New Jersey. My mom immigrated to the U.S. from Brazil in the ‘80s. We grew up in a mixed-language household, toggling between English and Portuguese. In middle and high school, my soccer team used to bounce between a combo of English, Spanish, and Portuguese both at practice and in games. We used our diversity of backgrounds as a competitive advantage.

On Career Insights

After college, I did a fellowship with Venture for America, which places recent college graduates in startups in cities that need job creation. My first job was with a pre-series A company in the EdFinTech space. There, my skills grew both wide and deep as some days we moved office furniture, some days we built software, and some days we spent the whole day getting customers rocking and rolling. 

Soon after, I discovered dbt. I was person #52 in the dbt Slack channel. As I became a better data engineer, I’ve tried to make dbt and data better, too. I’ve contributed to dbt core, the dbt-utils package, and together with my former GitLab colleague Taylor Murphy, we contributed our own dbt package. 

In 2018, I joined GitLab as their first data analyst. After moving into a data engineering role, I spent 6 months as interim Chief of Staff to the CEO before joining the Chief of Staff team. It was an incredible learning experience, and I loved every minute of it.  

After GitLab, I built the data organization at Netlify. I’m most proud of how diverse my team was there. We were a mostly female engineering team, half were LGBTQ, we had multiple people of color and two deaf team members. I worked hard to make it an inclusive environment and as a result, we were an incredibly high-performing team. We were able to successfully imbue a culture of data at Netlify, in a way that never existed prior, in large part because of the executive support of Dalia Havens and Elena Verna. You can have the best tech in the world, but all the hardest problems are people-related. Having champions who give you candid feedback and advocate for your work is so important to professional development. I hope my nine direct reports would say the same about me.

On Getting into Data

I studied political science in college. My senior thesis was about the gender composition of social groups and how that affects political engagement. I didn’t know this at the time, but I was already doing data analysis back then if you just remove the domain of politics from the equation. I used R as the language for my thesis, which is actually what helped me get my first job in tech. 

Later on, in my career, I realized that the hardest problems in data are more people-oriented than technical. How do you build happy, productive data teams that won’t churn? How do you establish a framework for thinking about future data work?  

In 2020, I gave a talk at Coalesce with my colleague Taylor Murphy (we’re a good team) around running your data team as a product team. We got so much incredible feedback from that talk and that was the first time I felt like the ideas that seemed straightforward to me were a big paradigm shift for others in the community. I had a similar experience in 2021, where I presented a team on Breaking Your Data Team out of the Service Trap, and I received similar feedback. 

Most data teams are failing, and I’m not sure most people know what to do about it. But, it’s terrible for the industry. Today, all companies are data companies, but without drastically shifting the paradigm of how people work- of how data teams are run and interact with the organization- we’ll find frustrated leaders who don’t feel any more data-informed than they did five years ago. 

One specific thing I care a lot about is data management. How do we build data leaders? People come into data, have no career advancement, so they move on out. We are churning data people more quickly than we can build them. This came from having spent so much of my career reporting to someone who didn’t understand my job and didn’t understand what they were asking of me. Data people need to have data managers who can help grow and build data careers and data opportunities.

On Working with Amplify

Sarah first introduced me to Amplify. I came to appreciate the Amplify vision for the space, the thoughtfulness of the Partners, and the care for the ecosystem. I believe the best- and most profitable- work is done with wholeheartedness. I loved that so many of the companies that I was closely watching for how the data space was going to evolve were already in the Amplify portfolio.

Now, as a team member, I’m excited for the myriad of ways I get to help those same portfolio companies grow and evolve.  From building effective data teams to building tools that help those data teams thrive, and a wide spectrum of data strategy problems in between, I’m here to support founders and team members with nuanced conversations. All of these are hard problems and there isn’t a one-size-fits-all playbook, but there are common pitfalls that can be avoided.

Founders can expect me to always be up for having thoughtful conversations about how to best measure success with data, the latest meme making its way through data Twitter or the pros and cons of a given metric. I promise to show up on time- and end on time- but be incredibly present every minute in between.  

If we’re meeting, there’s a high probability that my dog makes an appearance in the background (the OG coworker) and a 50/50 probability that I’m sitting on my patio. 

Don’t be surprised if I am staring down most of the time – I’m usually scribbling cursive notes with pen and paper.

On Life Outside of Work

Outside of work, in the mornings, I can usually be found enjoying my patio with a good book and a big cup of black coffee; in the afternoons, I am probably chasing my son or dog. My ideal Saturday is spent watching Army Football in good company, grilling burgers on the Blackstone, and munching on a charcuterie board throughout the game. After years of CrossFit PRs, I transitioned to spectator and can now be found starting most mornings on my Peloton.