Riyaz Shaik

Background

About Riyaz Shaik

I'm a Senior Data Engineer with over a decade of experience designing and implementing modern, scalable data ecosystems across cloud, big data, and real-time environments. Throughout my career, I've worked with industry leaders like 3M, Flagstar, CBRE, Johnson & Johnson, and Guardian—empowering teams to transform raw data into actionable insights and future-ready platforms. My expertise lies in building enterprise-grade data pipelines using modern tools such as Azure Data Factory, Databricks, Snowflake, PySpark, Apache Kafka, and Spark Streaming—delivering robust solutions across batch, micro-batch, and real-time use cases. I have a proven record of optimizing query performance, designing CI/CD pipelines for data workflows, and enabling analytics teams with structured, trusted, and high-velocity data. With hands-on experience in multi-cloud ecosystems (Azure, AWS, GCP) and deep knowledge of data modeling (Star & Snowflake schemas), streaming architectures, data lakes, and orchestration frameworks, I help organizations build intelligent data platforms that are secure, scalable, and automation-driven. I've led migrations from legacy systems to cloud-native data warehouses, created frameworks for streaming ingestion using Kafka and Spark, and architected ML-ready pipelines for advanced analytics and AI applications. My work consistently reduces latency, improves reliability, and enhances observability, enabling faster decision-making and innovation. As a builder, I don't just deliver pipelines—I create frameworks for analytics acceleration, governed self-service, and AI/ML operationalization. I thrive in fast-paced, cross-functional environments, collaborating with data scientists, architects, and product teams to shape data strategies that align with business goals. Always learning, always building—I'm passionate about data engineering because I believe clean, accessible, real-time data is the foundation for every intelligent business decision.