Ravi Gupta — Associate Consultant

Seasoned technology leader with 22+ years of experience delivering success across Digital Engineering, Product & Platform Development, Application Delivery & Support, Agile/DevOps Transformation, Customer Success, Practice Development, and Program Management. Adept at designing scalable, secure, and high-performing big data and cloud-native solutions. Core Competencies: Big Data Architecture & Engineering: Designed and delivered enterprise-scale big data solutions using Hadoop, Spark, Hive, and Iceberg. Built secure, high-availability clusters integrated with Kerberos and Ranger. Hadoop Ecosystem Expertise: Proficient in cluster setup, tuning, performance optimization, and security. Hands-on with HDFS, YARN, MapReduce, and backup/recovery strategies. Cloud Lakehouse Modernization: Led on-prem-to-cloud migration using Apache Iceberg on Google Cloud. Delivered support for time travel, ACID transactions, schema evolution, and open table formats. ETL & NoSQL: Strong knowledge of ETL frameworks like Talend, and experience with NoSQL databases including MongoDB, Cassandra, and VoltDB. DevOps & Automation: Built automated data pipelines using Terraform and Cloud Composer (Airflow) to enable CI/CD and zero-downtime deployments. ML & Data Science Exposure: Working knowledge of ML algorithms like regression, classification, and clustering integrated into data pipelines. Leadership & Delivery: Skilled in SDLC management, stakeholder engagement, and program governance. Strong analytical, problem-solving, and people management skills. Project Highlight – Iceberg Lakehouse Modernization on GCP: Spearheaded the transformation of a legacy on-prem data lake into a scalable cloud-native lakehouse architecture using Apache Iceberg on Google Cloud Platform. Architected Iceberg-based storage with support for time travel, schema evolution, and ACID compliance. Integrated Spark and Flink for unified real-time and batch processing. Configured Hadoop catalog on GCS and evaluated Polaris for managed Iceberg. Migrated terabytes of Hive-managed data with lineage and snapshot preservation. Enabled rollback, partition evolution, and metadata pruning for optimized query performance. Automated CI/CD workflows with Terraform and Airflow. Impact: Achieved 30%+ performance gain, improved data governance, enabled zero-downtime schema updates, and positioned the platform for future interoperability with Delta, Hudi, and other engines.

Stackforce AI infers this person is a Big Data and Cloud Solutions Architect with extensive experience in enterprise-level transformations.

Location: Pune, Maharashtra, India

Experience: 16 yrs 6 mos