Juhie R

I am a professional with a solid background in data engineering and analysis with 3 years of experience. My ability to collaborate with stakeholders and engage customers effectively makes me an asset in driving product development and commercial success.

Engineer – Data Analytics - Sasken Technologies - Bangalore

(2022-09)

• Real-Time Streaming Solutions: Built and deployed a real-time data streaming pipeline on AWS, using IoT Core, Lambda, and S3 to process live event data, enabling immediate insights on EV data.
• Developed an interactive webpage: Have developed a webpage from scratch which fetches data from AWS and stream real time data to monitor through a webpage which is viewed by hundreds of users in Techfest.
• Automated Data Pipelines: Developed and automated over 20 robust ETL/ELT pipelines using Azure Data Factory (ADF), integrating data from diverse sources like Azure SQL, Blob Storage, and on-premises systems into Azure Synapse and the Data Lakehouse, ensuring 99.9% data availability for analytics.
• Engineered End-to-End Data Solutions: Deployed comprehensive data solutions within Microsoft Fabric, streamlining the entire analytics lifecycle from ingestion to visualization and reducing time-to-insight by 30%.
• Optimized Big Data Processing: Optimized large-scale data processing by developing PySpark notebooks and fine-tuning Databricks cluster configurations, which decreased data transformation job execution time by 40% and reduced monthly cloud costs by 60%.
• Delivered Actionable Business Intelligence: Delivered interactive Power BI dashboards and reports that visualized key performance indicators for EV components of a major automotive industry leading to a 15% improvement in operational efficiency.
• Cloud Data Migration: Contributed to the migration of enterprise data from on-premises servers to the Azure cloud using Azure Data Factory, establishing a scalable and secure Data Lakehouse environment for future analytics projects.
• Advanced Analytics & Machine Learning: Executed comprehensive Exploratory Data Analysis (EDA) using Python to prepare complex datasets for machine learning, subsequently training and testing predictive models on EV data to forecast RUL of the components.
• Enhanced Data Quality and Integrity: Implemented rigorous data transformation and cleansing processes within ETL pipelines, which improved overall data quality and consistency, ensuring reliable data for all downstream reporting and analysis.

B. Tech - Information Technology - Anna University (2018 - 2022)