Youssef, a Paris-based solution engineer at Databricks, shares his three-year journey: from "where do I even start?" to mastering a rapidly evolving product portfolio.
Source: official Databricks documentation · Databricks announcement
In Youssef’s words
“I still feel I need to learn more because the technology keeps evolving. We're releasing tons of features every year so we need to master them all and learn about them all. It's so exciting—I've never been bored since I joined the company.”
“When I first joined, I thought 'this is an amazing product but where do I even start?' But as I gained knowledge and experience, I realized we have a phenomenal product where there's always something to learn and always something to innovate on.”
Chapters
- 0:00 — Youssef: Paris Solution Engineer at Databricks
- 1:09 — Databricks Founders and Open-Source Strategy
- 1:40 — Why Technology Matters: Delta Lake, Spark, MLflow
- 2:12 — Open-Source Adoption: Tens of Millions Monthly
- 3:16 — Delta Lake 3: Liquid Clustering and Time Travel
- 4:18 — Community-Driven Development
Frequently asked questions
What makes Databricks' open-source strategy unique?
Databricks was founded by the creators of Apache Spark and Delta Lake. The company believes in giving back to the community—all open-source technology (Spark, Delta Lake, MLflow) receives tens of millions of downloads monthly. This community-first approach is built into Databricks' DNA.
Why is it important that Databricks' technology is backed by open source?
Open-source backing means Databricks technology is transparent, vetted by thousands of contributors worldwide, and not locked behind proprietary walls. This creates good energy in the market, enables external companies to contribute, and allows developers to trust the underlying architecture.
What are the key features of Delta Lake 3?
Delta Lake 3 introduces Liquid Clustering for intelligent table organization and enhanced Time Travel capabilities. These features make it easy to optimize workloads, change table layouts, and recover from mistakes—key building blocks for a modern data lakehouse.
How rapidly is Databricks' product portfolio evolving?
Databricks releases new features continuously, making it challenging for even experienced solution engineers to keep up. The product evolution is driven by both innovation and community feedback, with new capabilities announced regularly at conferences like Data and AI Summit.
What advice would you give someone joining Databricks today?
Embrace continuous learning—the technology landscape at Databricks evolves rapidly. Focus on mastering core technologies like Delta Lake, Spark, and MLflow. Engage with the open-source community to understand both the technology and the people building it. You'll never run out of things to learn or innovate on.
Full transcript
Auto-generated from the video and lightly edited for readability. Timestamps link to the moment in the video.
Show full transcript (14 segments)
0:03I don't know if um Holly did you have someone to come on hey you how are you good good thank you nice of you nice of you to join us I'm super happy to be here so tell us how has your week been so far what are you looking forward to I'm really looking forward to see all the exciting features we're going to release this year I mean I've been
0:26expecting this day since like last year so it's my it's say uh my New Year's Eve New Year's Eve I love that Ari yeah tell us your name and and so I'm youf I'm a solution engineer at Databricks and I'm based out of Paris and this is my third year at Databricks yeah this is my third year too what do you like how have you been feeling since you know the
0:49first time that you went let's compare I mean to be honest it's I still feel I need to learn more because the technology keep evolving like we're releasing tons of features every here so we need to master them all and learn about them all and it's so exciting so I've never been bored since I joined the company I can agree with you on that because when I first joined
1:11I was like this is an amazing product but where do I even start but like as I you know gain more knowledge gain more experience we have a phenomenal product there's always something to learn there's always something to innovate on we have amazing co-founders who are super creative and I can definitely agree with you we're just getting bigger and better every single year yes speaking you know co-founders uh you know everyone Ali arson mate Reynold uh
1:36everyone uh open source Academia is huge I love your shirt Delta Lake but the creators of apachi spark uh you know uh Delta Lake incredible M slow it's really amazing because our technology is backed by open source like ml Flor as you mentioned Delta Lake Sparks so it's
1:58super amazing because like you meet like people who contribute and not only data break but also external people like come other companies and it's creating some good energy and it's disrupting the market and I truly believe that thata is still the future yeah and gets all of our open source technology gets tens of millions of downloads a month so when I
2:20joined Databricks I like what like I I used open source but didn't realize tens of millions a month yeah yeah I mean and we keep like following the trads on like LinkedIn on Reddit on Twitter and I've seen the community growing fast and be amazed by everything we are able to provide and also are able to contribute and the possibility to learn from the
2:43others and just learn to be the best and try and get the other feedback and implement it and that's it and I truly believe I still that D brecks has been built for by the community for the community that's I love that I love it well good so for for me you know I I'll talk ml flow I love it I I
3:06have a data science background uh you know worked before Databricks in Sports World you seen the movie Moneyball kind of tangentially using analytics to affect Sports and we're going to have the Texas world champion Texas Rangers on as a guest um so for me ml flow is awesome and that you have different models that you bring to production that um uh you want to experiment with
3:29different what called hyper parameters different uh versions who uh ran it who didn't when does it go to production but uh I want to hear more about Delta lake so I'm a big big fan of Delta Lake I've been like using it since I believe 2020 yeah wow and I've been like seeing like how it did evolve like with Delta 2 a lot of features has been added like with
3:52Delta Tre with liquid clustering with uniform I'm pretty sure we have many exciting announcements today and and like it's super easy to see how you can like optimize your workloads how you can change the layout how you can benefit from time travel in case you do something say wrong so I believe it's truly truly uh amazing and Delta is still I think a product that will shap
4:15the future for for still several years I believe well well great well we're getting the the quick wrap up so thank you so much welcome from Paris everyone from Paris all of Europe you want to shout out Paris totally appreciate it Yoo Paris yes you're the best PSG let's go take care bye all right so what are you most excited for about dayron AI Summit I'm really
4:39excited to network and connect with data practitioners coming from all the world I'm looking for all the New Gen stuff coming into I'm excited to experience my first ever Tech conference I'm looking forward to the of course the keynote from Ali and all of the latest product and AI Innovation we're bringing to our customers I'm looking forward to speaking again at the Summit about data quality management with s breaks yeah I
5:02look forward to meeting with the customers I'm just thinking we don't have enough recent announ on products so I think it's going to be uh it's going to be a long list right it's going to be exciting uh because it's going to be a great event and everybody is going to love it
Official Databricks resources
- Liquid clustering for Delta tables — docs
- Delta Lake documentation — docs
- MLflow on Databricks — docs
- Databricks Free Edition — product
- Announcing automatic liquid clustering (Databricks blog) — blog
Related
- Delta Lake 4.0: Connect, Clustering, Variant Type, Type Widening
- Mastering Delta Lake: Liquid Clustering, Time Travel & Vacuuming
- Liquid Clustering & Delta Lake Optimization: Author's Best Practices
- Delta Sharing Behind Firewalls: Private Endpoints Proxy Serverless NCC
- All Databricks video guides
- All tutorials & videos
Databricks Answers
Looking for a quick, source-backed answer? Browse Databricks Answers on the Databricks Data and AI Platform — direct, documentation-validated answers to common Databricks questions, curated by Youssef Mrini, Senior Developer Advocate at Databricks.