On January 5, I started at Google as a Software Engineer on the Napa database team.

Napa is Google’s internal large-scale data warehousing system built around log-structured merge trees (LSM-trees) for real-time data ingestion. Its key feature is maintaining materialized views that stay consistent as new data arrives across multiple data centers, supporting queries with sub-second latency on petabyte-scale datasets.

Why I’m Excited

Returning to database and storage systems feels right. My time in Engineering Productivity at Databricks and at Augment Code was inspiring, but storage and databases are where I started, problems I keep coming back to. They need to work, are challenging to get right, and have strong foundations in both research and engineering.

Last week, I got my first starter task: hunting down flaky tests. This is a systems software engineer’s comfort food. I’ve done that hundreds of times at Pure Storage.

This is also the first time I’m not joining a startup. Whether Databricks in 2021 was still a startup can be debated, but Google definitely isn’t. At Augment, I was employee 3, still working from the Sutter Hill Ventures office in Palo Alto. In many ways, small startups feel more natural to me, but after Augment I wanted something different: navigating a massive organization, understanding systems people have worked on for more than a decade, working at unprecedented scale.

This is what Gemini generated for me:

The Journey to Google

It wasn’t a direct path. The first time I applied was in 2008 during my Master’s studies. I interviewed at Google Munich, which at the time was a very small office with only a dozen or so engineers. I was rejected. Looking back, I wasn’t ready.

Over the years, I’ve done five full rounds of interviews with Google and passed three. This time, everything lined up.

Each step in my career prepared me for the next: the PhD taught me to think deeply about technical problems; Greenplum taught me distributed databases and legacy codebases; Pure Storage taught me high-performance systems, engineering discipline, and technical leadership. The genius of the FA architecture and the engineering talent during my early years at Pure are something I will cherish forever. At Databricks I learned about working in a sprawling, growing organization. Augment Code taught me AI infrastructure and working with LLMs before it was “cool”.

When I look at the Napa codebase now, I recognize patterns from Pure Storage’s “Pyramid”, see operational aspects from Databricks and Augment, and appreciate testing practices from my engineering productivity work.

The 2008 rejection wasn’t the end. It was the start of a journey that brought me here ready.