With 15+ years of industry experience and as the author of Data Engineering Design Patterns (O'Reilly), I bring a rare blend of deep technical expertise and proven pedagogical clarity to technical training. My career has been anchored in solving real-world data challenges, from architecting scalable systems to implementing cutting-edge tools—experience I translate into actionable insights for learners.

As a trainer, I specialize in three critical areas:

• Stream Processing with Apache Spark Structured Streaming: Master real-time data pipelines with industry-proven techniques, leveraging Spark's latest features to build fault-tolerant, scalable streaming solutions.
• Software Engineering Best Practices in Data Engineering: Learn how to apply design patterns, modular coding, and clean architecture principles to avoid technical debt and ensure maintainable, collaborative projects.
• Tests in Data Engineering: Implement robust testing frameworks (data quality, pipeline validation, unit/integration tests) to automate reliability and catch failures before they cascade.

My training philosophy prioritizes applied learning - combining theory with hands-on labs, real-world case studies, and hard-earned lessons from the field. Whether upskilling teams or mentoring professionals, I empower students to bridge the gap between theoretical knowledge and production-ready execution.

Let's transform your team's approach to modern data engineering—with precision, best practices, and an unwavering focus on results.

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