About

Gopi Kudaravalli is a seasoned Big Data professional and a certified Cloud Solutions Architect with over 7 years of relevant experience. He is passionate about smart data-driven technologies, platforms, products, applications, insights, and decision sciences. Gopi is currently working as a Technology & Innovation Leader in the Data & Analytics Practice at Quantiphi, where he is responsible for Principal Architecture for Data Modernization on Multi ☁️. Prior to this, he worked as a Big Data Solution Engineer at Vizio Data Analytics (DataOpt) and a Software Development Engineer at Princeton IT Services, Inc. Gopi's competencies include problem-solving ability, an engineering mindset, the ability to rapidly explore, design, architect, and implement solutions, bringing innovation to the table, leading engineering efforts & delivery, and capacity building. He is an innovation lead, mentor, and entrepreneur. Gopi's technology expertise includes Cloud Platforms such as Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure. He has experience with Hadoop Distros like Hortonworks Data Platform (HDP), Cloudera Distribution of Hadoop (CDH), Classic Apache, Elastic Map Reduce (Amazon EMR), Cloud Dataproc (Google), and Microsoft HDInsight. He is also proficient in Distributed Processing tools like MapReduce, Hive, Spark (SparkSQL, Streaming, Spark ML, PySpark, Scala), Google Big Query, Athena, Cloud Spanner, Presto DB, AWS Redshift, and Elastic Search. Gopi has expertise in Serverless Architecture, streaming tools like Spark Streaming, Apache Flink, Apache Kafka, AWS Kinesis, Storm, MiniFy, Google DataFlow, Pub/Sub, and infrastructure as code/automation/config management tools like AWS Cloud Formation, GCP Deployment Manager, Managed Instance Templates, Big Data Utilities, Cloud Break, Blueprints, Bash, Python, and Ansible. He has experience working with Data Pipelines like Hortonworks Data Flow (HDF), Apache NiFi, Talend, Stream Sets, Shell Scripting, Airflow, Oozie, and Google Dataflow. Gopi is proficient in Cloud Storage tools like Amazon S3, Google Cloud Storage, and HDFS (EBS Volumes, Persist Disks, S3, GCS), and Data Science Solutions such as R, Python, Spark, TensorFlow, Cloud ML, Vision API, DataRobot, Dockerized ML solutions, Serverless model deployments, and