shashipritham

• 9+ years of overall IT experience in a variety of industries, this includes hands-on experience as a data engineer in Big Data Analytics and development. • Extensive experience on migration tools such as Qlik replicate/ DMS. • Experience in collecting, processing, and aggregating large amounts of streaming data using Kafka, Spark Streaming. • Designed and implemented GCP data solutions resulting in 30% increase in customer satisfaction. • Good Knowledge on Apache NiFi for automating and managing the data flow between systems. • Experience in designing Data Marts by following Star Schema and Snowflake Schema Methodology. • Highly skilled in Business Intelligence tools like Tableau and PowerBI. • Experience in Spark-Scala programming with good knowledge on Spark Architecture and its In-memory Processing • Experience in designing and developing applications in Spark using Python to compare the performance of Spark with Hive. • Designed and built GCP cloud data solutions, big data platform services, serverless architectures, and Hadoop ecosystem for multiple clients. Delivered innovative Proof of Concepts for customers resulting in increased customer satisfaction and revenue. Led and delivered workshops and strategy sessions for customers working to solve their business use cases with innovative technology solutions. • Hands-on Experience in Service Oriented Architecture (SOA), Event Driven Architecture, Distributed Application Architecture and Software as Service (SAS). • Hands-on experience with Amazon EC2, Amazon S3, Amazon RDS, VPC, IAM, Amazon Elastic Load Balancing, Auto Scaling, Cloud Front, CloudWatch, SNS, SES, SQS and other AWS services. • Experience in working in Hadoop eco-system integrated to the Cloud platform provided by AWS with several services like Amazon EC2 instances, S3 bucket and RedShift. • Good experience working with Azure Cloud Platform services like Azure Data Factory (ADF), Azure Data Lake, zure Blob Storage, Azure SQL Analytics, Azure Databricks. • Good work experience with the cutting-edge technologies like Kafka, Spark, Spark streaming. • Partnered with cross functional teams across the organization to gather requirements, architect, and develop proof of concept for the enterprise Data Lake environments like MAPR, CLOUDERA, HORTONWORKS, AWS, and AZURE. • Experience in Data Pipelines, phases of ETL, ELT data process, converting BigData/unstructured data sets (JSON, log data) to structured data sets for Product analysts, Data Scientists. • Extensive knowledge of Spark Streaming, Spark SQL, and other Spark components such as accumulators, broadcast variables, various levels of caching, and optimization techniques for Spark employment • Strong Experience in analyzing data using HIVE, Impala, Pig Latin, and Drill. • Leveraged GCP storage services such as BigQuery, Google Cloud Storage, or Firestore to store and manage large volumes of structured and unstructured data for analysis. • Experience in designing a Terraform and deploying it in cloud deployment manager to spin up resources like cloud virtual networks, Compute Engines in public and private subnets along with AutoScaler in Google Cloud Platform. • Experience in writing custom UDFs in Hive and Pig to extend the functionality. • Experience in writing MAPREDUCE programs in java for data cleansing and preprocessing. • Excellent understanding/knowledge of Hadoop architecture and various components such as HDFS, Job Tracker, Task Tracker, Name Node, Data Node, Resource manager, Node manager. • Hands on experience on Data Analytics Services such as Athena, Glue Data Catalog & Quick Sight. • Significant experience with AWS, GCP and Azure Security. • Experienced in GCP features which include Google Compute engine, Google Storage, VPC, Cloud Load balancing, IAM • Experience using Azure utilities such as Azure Data Factory, Azure Data Lake and cloud watch to run and monitor Hadoop and Spark jobs on Azure. • Excellent understanding and knowledge of NOSQL databases like HBase, and Cassandra. • Experienced in converting Hive/SQL queries into Spark transformations using Spark Data Frames and Python. • Built ETL /ETL data pipelines, BI models, and dashboards on a public Cloud platform. Participated in deep architectural discussions to build confidence and ensure customer success when building new solutions and migrating existing data applications on the AWS, Azure, GCP, and Snowflake platforms. Mentored and trained other engineers within the organization on modern Big data and cloud-native Data Technologies. • Extensive experience in integrating various data sources like SQL Server, DB2, PostgreSQL, Oracle, and Excel • Developed JSON Scripts for deploying the Pipeline in Azure Data Factory (ADF) that processes the data using the SQL Activity. Build an ETL which utilizes spark jar inside which executes the business analytical model. • Experience with PySpark for using Spark libraries by using python scripting for data analysis. • Expose to various software development methodologies like Agile and Waterfall. • Designed and implemented both batch and real-time streaming data ingestion pipelines using GCP services like Cloud Storage, Pub/Sub, Dataflow, or BigQuery.