• Improved email performance by fine-tuning GPT-3, resulting in a 20% increase in open rates, 4% higher response rates, and a 2% boost in conversion rates.• Reduced expenses by 60% by developing an in-house T5 transformer to minimize reliance on costly OpenAI's GPT-3 for personalization of cold emails.• Collaborated on the Predictive Demand Generation (PDG) feature, training an ANN to identify potential buyers from a list with an AUC score of 0.81.• Enhanced business intelligence tool with AI-generated suggestions and sales campaign data plots, leading to up to a 10% increase in sales reported by users.• Designed and built automated pipelines, implementing end-to-end solutions for batch and real-time machine learning algorithms, including monitoring, testing, and performance optimization, in collaboration with cross-functional teams.• Developed notebooks using Databricks, Python, and Spark to extract data from Delta tables in Delta lakes.• Created Azure Data Factory and implemented policies to manage and ensure efficient storage and backup on Azure Blob storage.• Designed and maintained ADF pipelines with a range of activities including Copy, Lookup, For Each, Get Metadata, Execute Pipeline, Stored Procedure, if condition, Web, Wait, and Delete.• Extensive experience in migrating applications from internal data storage to Azure, including the development of streaming applications in Azure Notebooks using Kafka and Spark.• Implemented Slowly Changing Dimension Type 2 (SCD2) in Databricks to update or insert/delete data based on business requirements.• Developed a framework for creating new snapshots and managing the deletion of old snapshots in Azure Blob Storage and implemented lifecycle policies to back up data from Delta lakes.• Integrated framework and CloudFormation to automate the creation of Azure environments, leveraging build scripts (Azure CLI) and terraform for deployment on Azure.

• Designed and implemented AWS architecture, including cloud migration, AWS EMR, DynamoDB, Redshift, and event processing using Lambda functions.• Utilized Amazon EMR for efficient Big Data processing across a Hadoop Cluster on Amazon EC2 and S3.• Leveraged AWS services to develop robust big data analytics, enterprise data warehouse, and business intelligence solutions, ensuring optimal architecture, scalability, and flexibility.• Proficient in importing and exporting data into HDFS and Hive using Sqoop.• Utilized Impala and BI tools to run ad-hoc queries directly on Hadoop.• Leveraged Bash and Python, including Boto3, to enhance automation through Ansible and Terraform for tasks such as EBS volume encryption.• Utilized Terraform to migrate legacy and monolithic systems to Amazon Web Services.• Implemented Docker images and orchestrated Docker containers using ECS, ALB, and Lambda for multiple micro services.• Developed Spark scripts in Scala, including custom RDDs, for efficient data transformations and actions on RDDs.• Created metric tables and end-user views in Snowflake to support Tableau refresh.• Generated custom SQL queries to verify dependencies for daily, weekly, and monthly jobs.• Migrated MapReduce programs to Spark transformations using Scala.• Developed Spark code and Spark SQL/Streaming for faster data testing and processing.• Wrote Python modules to extract data from MySQL source databases.• Deployed Cloudera distribution on AWS EC2 instances.• Deployed projects on Amazon EMR with S3 connectivity for secure backup storage.• Created Jenkins jobs for CI/CD using Git, Maven, and Bash scripting.• Developed a regression test suite within the CI/CD pipeline, including data setup, test case execution, and tear down using Cucumber-Gherkin, Java, Spring DAO, and PostgreSQL.• Conducted ETL data integration, cleansing, and transformations using AWS Glue Spark scripts.

•Extensive experience in designing and deploying Hadoop clusters and various Big Data analytic tools, including Pig, Hive, HBase, Oozie, Sqoop, Kafka, and Spark, with a focus on Cloudera distribution.•Developed a scalable and configurable AutoML solution that optimizes features, algorithms, and hyperparameters, significantly reducing experimentation time by weeks.•Proficiently configured, deployed, and maintained multi-node Kafka clusters for development and testing purposes.•Well-versed in snowflake architecture and concepts, leveraging this knowledge to design efficient data systems.•Created a logistic regression model within GCP Big Query for classification purposes, showcasing expertise in leveraging cloud-based analytics platforms.•Skilled in building interactive visualization dashboards using Tableau, enabling insightful data exploration and analysis.•Developed an application that automates crop type prediction, plant identification, and detection of pests and fungi using image analysis techniques and neural networks. Successfully deployed this model in a web application.•Implemented computer vision algorithms, including YOLO, for insect detection in crops, enabling timely preventive measures.•Leveraged AWS DeepLens, Recognition, Greengrass, and Lambda to deploy object detection and movement detection capabilities in a web application, enhancing security and intruder identification.

• Implemented T-SQL tuning techniques and optimized queries for SSIS packages to enhance performance and efficiency.• Devised distributed algorithms to effectively identify and analyze trends in data, ensuring accurate processing and valuable insights.• Created an SSIS package to seamlessly import data from SQL tables into distinct sheets within Excel, streamlining data management processes.• Utilized Spark and Scala for developing machine learning algorithms capable of analyzing clickstream data, facilitating data-driven decision making.• Leveraged Spark SQL for preprocessing, cleaning, and performing joins on extensive datasets, ensuring data quality and integrity.• Collaborated in the co-development of SQL server database systems, maximizing performance benefits for clients, and improving overall efficiency.• Assisted senior-level data scientists in designing efficient ETL (Extract, Transform, Load) processes, including the development of SSIS packages.• Managed database migrations from traditional data warehouses to Spark clusters, ensuring smooth transitions and optimal utilization of resources.• Maintained data warehouse integrity by regularly conducting cleaning and integrity checks to ensure the inclusion of only high-quality data.• Utilized Oracle relational tables for process design, leveraging their capabilities to achieve efficient data management and analysis.• Developed SQL queries to extract data from existing sources, validating the accuracy, and formatting of the retrieved information.• Created automated tools and dynamic dashboards to capture and display real-time data, enabling efficient data visualization and analysis.• Coordinated efforts to address data security concerns and provided guidance to other departments on secure data transmission and encryption protocols.