Azure Data - Microsoft Fabric Telemetry Infrastructure

▪ Technologies & Tools: R, Python, SQL, Tidy-verse, Tableau, Shell scripting▪ Responsibilities: • Design data storage model and pipelines to enable efficient retrieval and storage of institute’s research data. • Generate data quality reports to provide a holistic view of the available data. • Contributing to the creation of operation manuals and documentations for institute’s data access and usage. • Perform analysis on the data and develop reports to answer research questions. • Developed a standard entity resolution framework to match and link records across multiple unconnected datasets. • Develop framework to enable data access to researchers without exposing PIIs.

Project #1: Reporter Dashboard▪ Technologies, Tools and Frameworks: OBIEE, TFS, Informatica, Oracle, Unix, Agile, Scrum, SSAS, Tableau, PowerBI, Scrum▪ Responsibilities: • Plan design, develop, and test high quality end-to-end business intelligence solutions following agile design lifecycle. • Gather business requirements, follow up on existing projects and ensure deliveries meet stakeholder expectations. • Act as Subject Matter Expert for Finance and HR domain and primary point-of-contact for product development staff. • Monitored database performance and optimize queries for 50% reduction in query time. • Created reports to monitor KPI and Data Quality Metrics. • Mange existing data warehouse and contribute to the design and development of next generation Enterprise Data Warehouse. • Developed Reports using OBIEE, PowerBI and Tableau to answer business questions.Project #2: ETL Migration to Cloud ▪ Technologies: Hadoop, Spark, Hive, Azure Data Flows, Azure Data Factory, Azure Synapse, SSIS, Python▪ Responsibilities: • Developed scalable ETLs and SQL to transform data using cloud data infrastructure. • Optimized existing queries and ETLs and SQLs to run on MPP databases to gain 70% performance improvement. • Developed pipelines using Databricks Spark for time sensitive data processing projects. • Conduct PoC using Hadoop, and Hive for Big data analytics projects. • Developed audit and control framework to execute, log and monitor status of all data processing jobs. • Automated restart of data processing pipelines, saving 40% time in manual interventions for restart. • Contributed to the creation of a standard technical operational manual for data migration projects to Cloud. • Developing CI/CD pipelines for build, test, and deployment. • Mentor interns and college grads, providing them hands on experience on the tools and providing feedback for improvement.