AWS Summit Madrid 2025 - A Day Full of Data, AI & Real Tech Vibes
| 17 Jun 2025This year, I finally attended my first AWS Summit in Madrid, and honestly? It was totally worth it!
As a data engineer who works with AWS every single day, this event felt like the perfect opportunity to take a step back from day-to-day work, learn something new, and reconnect with the tech community. Plus, being held close helped seal the deal.
I’ve been to other tech conferences before (like the Global Software Architecture Summit or GSAS in Barcelona, BilboStack in Bilbao, or TechFest in Madrid), but I was really curious about what an AWS-hosted event would feel like. I wondered if it’d have more of a local or global vibe—and the answer is a bit of both. There was definitely a strong Spanish presence, which made it feel familiar and connected. And in terms of scale, this was a level above most events I’ve attended.
The Setup: Smooth, Massive, and Well Organized
The event was really well put together. Clear signage, well-marked zones, and the tracks were divided by theme, which made it easier to find content that matched your interests.
One thing that totally blew my mind: 11 tracks running in parallel. All of them full. A great sign that there’s real interest in AWS topics across the board. You can check out the full agenda here if you’re curious.
The crowd? A great mix: data engineers, developers, architects, CTOs, and even folks with more business-oriented profiles. You could feel the energy—lots of curiosity, innovation, and excitement in the air.
Talks That Stuck with Me
It’s tough to choose, but here are three sessions that I personally found insightful and relevant:
1. Event-Driven Architectures at Scale – Iberia Airlines Case
Speakers: Miquel Llorca (AWS), Alfredo Moreno & Ildefonso Serrano (Iberia)
This talk explored how Iberia transformed their systems using Amazon EventBridge and a scalable, event-driven approach. What stood out to me: the way they tackled centralized vs. decentralized event architectures and how that decision ties directly to how your teams are structured. Also loved the deep dive on schema evolution, which is often overlooked in theory but super important in practice.
As someone who deals with real-world data pipelines, seeing this kind of implementation was super valuable. Lots of takeaways I can bring back to my own projects.
2. Understand your Customers better with a Modern Data Strategy
Speaker: Juan Carlos “JC” Ruiz (AWS)
This one was more of a walkthrough across AWS data services—from ingestion to analytics and prediction. What made it special? JC’s style. He gave this session in a smaller theater, which made it feel more like a conversation than a lecture. Super clear, super practical and very approachable.
This talk actually made me rethink how we’ve structured our internal datalake and gave me ideas for a PoC we might try soon. Worth it just for that spark alone.
3. Modernizing BI with QuickSight – BBVA Case
Speakers: Andrés Castro (AWS), Pablo Espinosa & Ángel Montero (BBVA)
Okay, I’ll admit it: this was a bit personal. I work at BBVA, so I already knew the project being presented—but that’s exactly why I went. I wanted to see how we communicated it externally and how the story came together from a higher-level view. It gave me new context and helped me understand decisions that, from the inside, sometimes feel abstract.
💡▶️ Bonus: Want to watch the sessions on demand? They’re available here: 🔗 https://summitmadrid.awslivestream.com
Trends Worth Noting
There were clear themes that dominated the event:
- Generative AI everywhere — demos, use cases, service integrations.
- A strong focus on data, analytics & lakehouses
- Push toward serverless and managed containers
- Security and cost optimization mentioned in almost every architecture session
If I had to guess what’s coming next, from a technical standpoint:
- Companies will double down on GenAI—but with managed tools like Amazon Bedrock, rather than building everything from scratch.
- We’ll continue seeing less infrastructure to manage, with serverless and containerized workloads becoming the default.
- The Lakehouse model is slowly becoming the new normal, thanks to Iceberg, Glue Crawlers, and native integrations.
My Take as a Data Engineer
👍 What I liked:
- Lots of data and AI content — not everything was infra-related.
- Real case studies that actually went deep into architecture decisions and challenges.
- Strategic context: I got a clearer picture of where AWS is heading with analytics and GenAI, which helps me make more informed decisions for evolving our environments.
- Validation of approaches: Hearing how other companies solve similar problems with tools I use gave me confidence and fresh ideas.
- And hey, some great swag: AWS socks and a Red Hat fedora hat 😄
👎 What I didn’t love:
Some talks (mostly from partners or sponsors) felt a bit too salesy and light on technical depth. The good thing is that you can usually spot them early and jump to another track.
🔄 What I’d do differently next time:
Honestly? Less running between tracks, more networking. The sessions are all recorded, but the random conversations you have in between—that’s where a lot of value happens. Next time, I’ll plan fewer talks and leave more space for hallway chats.
Final Thoughts: Would I Recommend It?
Absolutely. If AWS is part of your day-to-day, this summit gives you the big-picture view, technical inspiration, and just enough tactical detail to walk away with ideas you can actually implement. I left with new perspectives, new questions—and a lot of notes I’m already revisiting.
Have you attended an AWS Summit recently or are planning to? I’d love to hear your thoughts or experiences! Feel free to reach out and chat with me anytime via DM on my GitHub profile. 😊💬