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Gregory Wood
Security, DR & Platform @ Databricks
Gregory Wood is currently the Enterprise Platform Lead at Databricks, a role he has held since October 2021. He is based in the New York City Metropolitan Area and has a strong background in data solutions and cloud technologies. Prior to his current position, he served as a Senior Solutions Architect at Databricks from September 2018 to October 2021, where he was responsible for guiding clients through the technical customer lifecycle, focusing on various industries including healthcare, pharmaceuticals, and finance.12
In his role as Enterprise Platform Lead, Wood emphasizes the importance of cloud security and innovation, ensuring that patient data is managed effectively while meeting modern architectural demands. His expertise includes advanced dashboarding, big data integration, and rapid prototyping for custom use cases. He has also contributed to improving processes and capabilities within his teams, showcasing his commitment to education and knowledge sharing in the field of data analytics.1
Wood's career prior to Databricks includes positions such as Field Sales Engineer at Zaloni and Senior Consultant at Apptio, where he focused on delivering technical solutions and driving revenue growth through innovative data technologies.12
Highlights
As I start to round the corner on 6 years at Databricks, I reversed my Gmail order to see what some of the first emails I received looked like. Here's what I found:
- A report touting that MLflow had 1 company using it daily. One! Not counting the 6 early-preview alpha customers
- Many, many emails sporting a spiffy Spark+AI Summit Europe 2018 banner, as we were about a month away from that event (which no longer exists)
- Multiple emails talking about the recent earnings of Cloudera as they approached 1.5 years of being a public company (!) and the upcoming IPO of Elastic
- Perhaps most shockingly, most of our customers would just send an email to our sales email alias (which the entire company would then receive) when they needed something. It worked, AND... we somehow did it without creating 50-email CC storms
Sometimes, I think 6 years isn’t that long. Then I do something like this and realize that it’s really, really long. 6 years ago, I was still in Boston, with no idea about how crazy life would soon become. Databricks was still the “Unified Analytics Platform” company with about 500 employees and our biggest competitors were Cloudera, EMR, and HDInsight. GenAI had not entered the public lexicon, and Coronavirus was still just something you got from drinking a bad beer. We lived in a fundamentally different world.
At the same time, some things have stayed the same. Databricks isn't a lean startup anymore (16x growth will do that), but it is still a great place to work, and still has some of the smartest people I’ve ever seen assembled in one place. I’m still eternally grateful that Vida Ha and Arsalan Tavakoli took a chance on me. I still can’t believe I ended up here after a start in RF systems, of all places (this one is especially crazy considering I’m now back in the same city in which I started my career). And of course, I still enjoy a good post-bike IPA (although a 16 month old and 6 trips around the sun have changed what that looks like).
Cheers to 6 years Databricks- looking forward to seeing what 6 more bring.
(Unfortunately I couldn't find any pictures of our original, tiny Cambridge Wework office, but here's my first picture in the SF HQ, back when we still only had one or two floors. I still miss that OG logo)
I get asked about optimizing #cloudstorage costs a LOT- it's far and away the most common topic I hear from customers. And when storing a couple of tables for a year can run you about the same as a new car, I get it! After a recent conversation, I decided to write up some thoughts on one of the newer features of #DeltaLake, Archival Support. Combined with Deep Clone, it can let your poor business continuity team sleep at night knowing your data is backed up, AND let you get that fancy new espresso machine for the office! Give it a read on the Databricks Platform SME Medium Channel.
