Fawaz Ghali
Snowflake, Lead Developer Advocate - EMEA
London, United Kingdom
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Fawaz Ghali is a technologist specializing in AI, Data Engineering, Open Source, and Developer Relations. Passionate about community-driven innovation, he creates technical content, delivers talks, and engages with developer communities to drive the adoption of modern technologies in a rapidly evolving landscape.
With over two decades of experience and a PhD in Computer Science, Fawaz has published 45+ peer-reviewed papers and delivered 200+ talks worldwide. He is also the author of several books and reports and actively shares insights, empowering developers and data engineers through knowledge-sharing and collaboration.
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Seamless PostgreSQL and MySQL Integration in Snowflake
Bringing OLTP data from PostgreSQL and MySQL into Snowflake for AI and analytics has never been easier. This session explores Snowflake’s new low-latency database connectors, built on Snowpipe Streaming, enabling seamless CDC-based data replication. Learn how to leverage these connectors for AI-driven insights, optimize ingestion pipelines, and simplify operations. Discover real-world use cases and best practices to unlock the full potential of your transactional data in Snowflake’s AI Data Cloud.
Building Scalable and Secure AI Solutions with Snowflake Arctic LLM and Streamlit
Using open-source tools like Snowflake Arctic LLM and Streamlit, organizations can create customizable, high-performance AI solutions without the limitations of proprietary software.
This session will demonstrate how Arctic LLM and Streamlit support secure, interactive AI development—from chatbots to workflow automation—while offering flexibility, scalability, and reduced costs, all with full transparency. Join us to learn how open-source tech can drive efficiency and innovation in AI for financial institutions.
Generative AI for Scalable Data Pipelines with Streamlit
In this session, you'll learn how to build a Streamlit app to generate personalized messages using AI. Gain hands-on skills in setting up Streamlit and Snowflake, creating AI-driven content, and developing a user-friendly app that drives data-powered personalization.
Perfect for developers and data engineers, this talk will equip you with practical insights to leverage generative AI for scalable and impactful marketing strategies.
Feast Feature Store for AI Pipelines
In this session, we’ll explore how Feast and Snowflake work together to build a powerful feature store that bridges batch and real-time AI workflows. You’ll learn how to efficiently store, process, and serve ML features with minimal data movement, optimizing both model performance and deployment speed.
Attendees will gain practical insights into streamlining end-to-end AI workflows, from data ingestion to model deployment. This session will equip you with the knowledge to optimize feature engineering pipelines and drive faster, more efficient AI model deployment.
Harnessing LLMs and AI Agents with Streamlit and Snowflake Cortex
In this session, AI and data engineers will learn how to build powerful AI-driven applications using Streamlit and Snowflake Cortex. Step by step, discover how to integrate Large Language Models (LLMs) and intelligent agents into data pipelines to automate workflows and generate real-time insights.
Learn to leverage Streamlit and Snowflake Cortex for seamless AI integration and use Streamlit to create intuitive, interactive tools that bring data to life. By the end, gain the skills to build scalable AI applications that elevate data engineering projects to the next level.
Data Lakes Unlocked – Apache Iceberg with Python and SQL
Big data demands big solutions—but traditional data lakes often fall short on performance, consistency, and scalability. Enter Apache Iceberg: an open-source table format designed to bring ACID transactions, schema evolution, and high-performance querying to modern cloud-native data architectures.
For Python developers and data engineers, Iceberg offers powerful capabilities for managing massive datasets efficiently. Whether you're ingesting, querying, or evolving data, Iceberg ensures transactional integrity, optimized performance, and seamless integration with various compute engines.
From time travel and partitioning strategies to best practices for scalable data lakes, this session will demystify Apache Iceberg and provide the insights you need to build future-ready, cloud-native data pipelines.
Cloud Data Scaling – Smart Search and Automated Optimization
AI is transforming industries, but scaling AI in the cloud requires balancing performance, security, and cost efficiency. As organizations adopt LLMs, intelligent search, and automated model tuning, they must implement strategies that ensure scalability and governance while unlocking AI’s full potential.
This session explores the latest advancements in cloud-based AI, revealing how businesses can optimize AI models, integrate AI automation into data pipelines, and enhance decision-making with intelligent search and document processing. Attendees will leave with a clear roadmap for deploying scalable, high-performance AI solutions that drive real impact.
Hands-On: Revolutionizing Data Pipelines with Dynamic Tables
Traditional data pipelines often demand constant maintenance, scheduling, and performance tuning, creating bottlenecks that slow innovation. Snowflake’s dynamic tables eliminate these challenges by automating pipeline management with declarative SQL, enabling fast, flexible, and scalable data processing.
In this hands-on session, you'll learn how dynamic tables simplify orchestration, optimize incremental processing, and seamlessly transition between batch and streaming workloads. Walk away with practical strategies to automate and scale pipelines, reduce costs, and ensure real-time data freshness—without the manual overhead.
Mastering Iceberg – The Java Engineer’s Guide to Data Lakes
Data lakes are evolving, and so should the way we manage them. Apache Iceberg is redefining data lake architecture with ACID compliance, schema evolution, hidden partitioning, and time travel, delivering the reliability and performance that modern workloads demand.
For Java developers and data engineers, Iceberg provides a powerful yet flexible framework to build scalable, high-performance data lakes without the complexity of traditional solutions. From CRUD operations to snapshot management and seamless integration with Apache Spark, Flink, and Trino, Iceberg enables better data consistency, simplified queries, and optimized storage—all while future-proofing your architecture.
The future of data lakes is here—efficient, resilient, and built for scale. It’s time to master Apache Iceberg.
Serverless Data Pipelines – Integrating LLMs with Data Platforms
Writing complex SQL queries is a challenge for many data teams, while business users struggle to extract insights without technical expertise. By integrating serverless Large Language Models (LLMs) within modern data platforms, organizations can enable natural language-driven analytics and democratize data access.
This session will explore how to implement serverless LLMs for SQL generation, optimize prompt engineering for accurate insights, and build interactive data applications using Streamlit. Attendees will gain practical strategies to move beyond traditional query methods and create AI-powered tools that simplify data exploration and decision-making.
Scalable Python and SQL Data Engineering without Migraines
Data is growing. Complexity is rising. Performance can't be an afterthought. Snowflake’s cloud-native architecture delivers unmatched scalability, real-time analytics, and cost-efficient performance—but to truly unlock its power, you need the right tools and strategies. Enter Python: the go-to language for data engineers, analysts, and AI practitioners.
This session will bridge the gap between raw data and actionable insights, showing how Python developers can seamlessly integrate with Snowflake to build scalable data pipelines, optimize performance, and harness advanced features like Snowpark, time travel, and zero-copy cloning.
From fast querying and automation to AI-driven transformations, this talk will provide the strategies and best practices you need to scale your analytics and maximize the full potential of Snowflake and Python.
Data Storytelling – Turning Raw Data into Interactive Insights
Data doesn’t have to be boring—it should captivate, engage, and inspire! In this high-energy session, we’ll transform raw numbers into stunning visual narratives that make an impact. Using Altair, Matplotlib, and Plotly, you’ll learn how to craft eye-catching visualizations, weave compelling data stories with Markdown, and bring everything to life with interactive dashboards in Streamlit.
Forget static charts—this session is about making data storytelling dynamic, fun, and unforgettable. Whether you’re an analyst, data enthusiast, or storyteller, you’ll leave with the tools to turn insights into experiences that truly resonate.
Cloud-Native Data Lakes – Apache Polaris for Scalable Java Workloads
Big data isn’t slowing down, and neither should your data infrastructure. Apache Polaris is redefining what’s possible in cloud-native data lakes—combining ACID transactions, schema evolution, and scalable performance to handle massive datasets with ease.
For Java developers and data engineers, Polaris offers a next-generation, transactional approach to data lake management. With seamless integration into Apache Spark, Flink, and other compute engines, it enables efficient data ingestion, querying, and evolution—without compromising reliability.
As data complexity grows, traditional solutions fall short. Polaris future-proofs your architecture, ensuring flexibility, consistency, and speed in modern cloud environments. It’s time to rethink data lakes—faster, smarter, and built for the cloud.
Fawaz Ghali
Snowflake, Lead Developer Advocate - EMEA
London, United Kingdom
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