• Implemented End to End Robotic Process Automation (RPA) using UIpath.• Developer the objects and workflows as per client requirement.• Performed tool evaluation and feasibility to help in selecting suitable Automation tool for RPA implementation.• Designed, tested and developer Bot Tasks using RPA UIPath.• Worked with the Business Analysts in identifying and defining the requirements.• Analyze the feasibility of existing process suitable for automation.• Participated in Online meetings to demonstrate the capabilities of RPA for ongoing projects and potential clients.• Provide knowledge transfer/support/Assistance to the application development and support team.• Used UIpath Automation elements such as Mouse, Keyboard and attribute to automate the desktop sequence activities.• Image-Based texts in applications are also automated with mouse clicks,• Used screen Scraping method to extract text from running windows application by appropriate output methods such as native, full text and OCR.• Configuring new processes and activities using core workflow principles that are efficient, well-structured and manageable.• Handled the Execution of project in UIpath Robot.

• Developed and maintained ETL data pipelines in Azure Data Factory and architected solutions with Azure Synapse Analytics.• Integrated machine learning models using Azure ML and optimized big data processing with Apache Spark.• Implemented Lakehouse architecture in Google Cloud, handling data ingestion, organization, governance, security, and analytics.• Worked on AWS data pipelines with Python, PySpark, EMR services, and Glue jobs, focusing on migrating data to cloud storage and Redshift.• Provisioned infrastructure using Terraform, managing Azure Kubernetes Service (AKS) and optimizing workloads through autoscaling and monitoring with Prometheus and Grafana.• Migrated on-premise databases to Azure Synapse Analytics, resulting in improved query performance and cost savings.• Built Power BI dashboards from data in Azure Synapse, collaborating with cross-functional teams for reporting and business intelligence solutions.• Used dbx to develop and test Spark applications, creating efficient ETL jobs and defining workflows in YAML configurations.• Automated jobs using ADF triggers and created scalable data solutions for real-time analytics, while ensuring data security and compliance.• Developed Databricks ETL pipelines using notebooks, Spark DataFrames, SPARK SQL, and Python, while leveraging Cosmos DB for event sourcing and catalog data storage.

• Implemented an enterprise data warehouse solution using Azure Synapse Analytics for streamlined data storage, processing, and business intelligence reporting.• Designed and optimized ETL pipelines using Azure Data Factory and Azure Data Lake, ensuring efficient data flow and transformation from multiple sources, including SAP BW, SAP HANA, and AWS S3.• Collaborated with data scientists to integrate machine learning models into Synapse Analytics, enhancing predictive analytics capabilities for business operations.• Established robust data governance and security frameworks within Azure Synapse, ensuring compliance with organizational and regulatory standards.• Conducted extensive performance tuning and query optimization to handle large-scale data sets, ensuring efficient data processing and query execution.• Developed real-time streaming pipelines using Azure Event Hubs and Stream Analytics to analyze IoT data for dealer efficiency at USAA’s gaming tables, leading to actionable business insights.• Utilized Terraform for infrastructure provisioning, automating the deployment of Azure Kubernetes Services (AKS) and other cloud resources like Virtual Machines and Log Analytics.• Developed and optimized ETL pipelines in Azure Databricks, using Spark SQL, PySpark, and notebooks to process and transform large volumes of data from relational databases and cloud sources.• Collaborated with Power BI teams to build and validate data models, generating dynamic reports and dashboards for real-time business insights.• Automated the CI/CD pipeline using dbx integrated with tools like Jenkins and GitLab CI, ensuring seamless deployment and version control across Databricks clusters.

• Developed, deployed, and executed Spark jobs on Hadoop clusters using Python to process large-scale data on Hortonworks. Managed over 250 TB of batch data and 50GB of streaming data monthly.• Used SSIS for end-to-end data migration, including ETL processes, data warehousing, data governance, and big data integrations.• Designed and implemented ETL pipelines with Azure Synapse Analytics for comprehensive data analysis, integrating various data sources.• Developed business intelligence solutions by creating dashboards and reports in Power BI, allowing stakeholders to visualize key metrics and make informed decisions.• Automated data workflows and data quality checks using Python and Shell scripts, ensuring high data integrity.• Integrated Terraform and Kubernetes for efficient infrastructure management, deploying Azure resources and setting up autoscaling for Azure Kubernetes Services (AKS).• Ingested and transformed large datasets using Databricks, Spark SQL, PySpark, and Hive, optimizing data processing with partitioning, vectorization, and bucketing techniques.• Created Glue jobs to pull dimensional data from Oracle databases and upload them to AWS S3 for further analysis and integration with Salesforce.• Implemented disaster recovery and failover systems in the cloud by replicating data across regions, ensuring data availability and reliability.• Collaborated with teams to gather business requirements and provided analysis reports, optimizing Spark jobs and monitoring performance using Azure HDInsight.

• Involved in the implementation of design using vital phases of the Software development life cycle (SDLC) that includes Development, Testing, Implementation and Maintenance Support.• Used SSIS to create daily ETL pipelines for Data Warehousing, data migration pipelines, incremental data load pipelines, data synchronization pipelines, data cleansing and standardization pipelines, master data management (MDM) pipelines, real time data processing pipelines, data integration pipelines for bi and analytics, event driven pipelines, data archiving pipelines, data transformation pipelines for reporting, pipeline orchestration and workflow management, data validation and quality assurance pipelines, integration with third party APIs, batch processing pipelines. • Strong experience creating real time data streaming solutions using Apache Spark Core, Spark SQL & Data Frames, Spark Streaming, Kafka. • Excellent understanding /knowledge on Hadoop (Gen-1 and Gen-2) and various components such as HDFS, Job Tracker, Task Tracker, Name Node, Data Node, Resource Manager (YARN). • Proficient at using Spark APIs to cleanse, explore, aggregate, transform, and Store, sale, customer, and stock data.• Hands-on experience with message brokers such as Apache Kafka.• Hands-on experience with systems-building languages such as Scala, Java.• Experience in writing UNIX shell scripts. • Involved in Requirement Analysis, Design, Development and Testing of the risk workflow system.