Chandrakanth Lekkala

I’m a passionate Cloud Architect and Data Engineer with a focus on simplifying complex data ecosystems. I specialize in designing scalable pipelines and optimizing cloud-native architectures across platforms like GCP, Azure, and Snowflake enabling seamless integration between data infrastructure and machine learning systems. In addition to engineering, I contribute to the broader data community as a technical author, peer reviewer, and occasional speaker. I’ve been invited to evaluate national-level AI competitions and currently serve on the editorial boards of respected journals in the fields of data science and computing. My recent work focuses on large-scale data ingestion, efficient data partitioning techniques, and cloud-native data lineage and governance frameworks leveraging technologies like Spark, Snowflake, Databricks, and Kubernetes. I emphasize real-world applicability, platform scalability, and automation of data workflows to support AI/ML-driven use cases. I’m committed to mentoring emerging talent, sharing practical insights, and continuously evolving with the fast-changing data and AI landscape.