Aris Kaisaris is a Lead Data Engineer at Netcompany, specializing in financial services and enterprise data architecture. With expertise in Databricks, Spark, SQL Server, Power BI, and Azure, he designs and delivers AI-ready data platforms for Tier-1 banking clients. He leads a team of data engineers building real-time analytics and machine learning infrastructure, and contributes to Netcompany’s central Data Management & BI practice across banking, energy, and public sector projects.
Aris Kaisaris is a Lead Data Engineer at Netcompany, specializing in financial services and enterprise data architecture. With expertise in Databricks, Spark, SQL Server, Power BI, and Azure, he designs and delivers AI-ready data platforms for Tier-1 banking clients. He leads a team of data engineers building real-time analytics and machine learning infrastructure, and contributes to Netcompany’s central Data Management & BI practice across banking, energy, and public sector projects.
Explores how banks can evolve lakehouse platforms into AI-ready production architectures using Databricks and Apache Spark, with governance, regulatory, and operational patterns.
Most AI projects in a bank don’t get stuck on the model. They get stuck on the data underneath it. The lakehouse is the base, but it is not enough. This session shows what has to change in a data platform when models and agents consume data in production—not just dashboards and reports—and how to architect it on Databricks and Apache Spark.
• Part 1: Architecture & Banking Context (25 min) – Aris Kaisaris
– 4 places where AI ideas get stuck
– 4 properties for AI-ready platforms
– Real cases from Greek banks
– Regulatory context (BCBS 239, DORA, EU AI Act)
• Part 2: Technical Deep-Dive on Databricks (30 min) – Konstantinos Segredos
– Reference architecture
– History (SCD2), Meaning (governance), Outcomes (logging)
– Production patterns and what breaks in PoC
• 3 Debate Statements + Q&A (5 min moderation)
A discussion of building global success and how artificial intelligence is transforming the world.
AI is transforming software development, making coding, knowledge, and execution more accessible than ever. As AI evolves from a productivity tool into the interface between human intention and creation, a deeper question emerges: what does it mean to be a capable human in the age of AI?
When a junior engineer can achieve in hours what once required years of experience, what truly distinguishes a senior professional? Is it technical expertise, or the ability to exercise judgment, ownership, critical thinking, creativity, and empathy?
This panel explores how AI is reshaping careers, learning, leadership, and human value. Where does deep expertise still matter? What skills remain scarce when knowledge and execution become abundant? And how should developers, students, HR leaders, and CTOs prepare for a future where anyone can build, but not everyone can create value?
Audience takeaway: Understand how the definition of talent, expertise, and impact is changing, and what skills will matter most in the AI-native world.
A hands-on workshop on using modern AI tools with WordPress for design, development, site management, and context-aware user experiences.
An interactive workshop examines how AI coding assistants and autonomous agents are reshaping software development, developer roles, and the skills needed to remain relevant.
A 60-minute AI-guided workshop builds and deploys an Airbnb-style booking MVP with Next.js, Tailwind CSS, and browser-based AI IDEs.
Architectural Katas give teams repeated practice designing systems, defending decisions, and learning from alternative approaches to develop architectural judgment.
A hands-on workshop using Elephant Carpaccio to practice vertical slicing, incremental delivery, and keeping software deployable through small end-to-end changes.
A hands-on workshop teaches context engineering for AI coding tools through prompts, project configuration, context management, and grounded retrieval.
