Harish Bharadwaj Email and Phone Number

• Designed and implemented scalable data solutions on Azure leveraging PySpark and Databricks, resulting in a 30% boost in data processing efficiency and a 20% cut in storage costs.• Constructed robust data integration pipelines from over 5 sources using Azure Data Factory, ensuring a 99.9% data consistency rate and high data quality.• Implemented more than 10 ETL and ELT processes using PySpark and Azure Data Factory, leading to a 25% increase in data ingestion speed.• Worked collaboratively with cross-functional teams to translate data requirements into technical solutions using Databricks and PySpark, enhancing data accessibility and usability.• Optimized data storage and retrieval by utilizing Azure Data Lake Storage, achieving a 40% reduction in data retrieval times and enabling real-time reporting capabilities.• Ensured full compliance with data protection regulations and maintained a zero-data breach record through robust security measures and governance frameworks implemented in Azure.• Managed and optimized data warehouses that supported over 1000 concurrent users using Snowflake and Azure Synapse Analytics, storing more than 100TB of structured and unstructured data efficiently.• Developed over 50 Power BI reports and dashboards, delivering actionable insights for informed decision-making across the organization.• Stayed updated with industry trends in Azure data services, leveraging PySpark and Azure Data Factory to drive continuous improvement and enhance business agility.Tech Stack: Azure, Pyspark, Databricks, ETL/ELT, Data Integration, Data Governance, Power BI, Security Compliance.

• Orchestrated the seamless collection and integration of data using PySpark within Azure Data Factory, pulling from diverse sources like databases, APIs, and flat files, thus establishing a comprehensive data ecosystem.• Played a pivotal role in developing robust data pipelines and ETL processes leveraging PySpark, ensuring efficient data transformation and loading into storage systems, leading to a 20% reduction in data processing time.• Conducted meticulous data cleaning and preprocessing tasks using PySpark within Azure Data Factory, resulting in a 15% improvement in data quality, consistency, and integrity, thereby enhancing overall decision-making accuracy.• Demonstrated proficiency in creating and maintaining data models and schemas using PySpark, optimizing data organization and structure within Azure Data Factory, contributing to a 25% increase in data accessibility.• Collaborated in designing both relational and non-relational databases tailored to project requirements, leveraging PySpark and Azure services, thus enhancing data storage efficiency by 30%.• Utilized advanced SQL queries and PySpark for data analysis within Azure Data Factory, providing valuable business intelligence insights that informed strategic decisions and improved operational efficiency.• Assisted in the development of dynamic data visualizations and interactive dashboards using tools like Power BI and Amazon QuickSight, collaborating with PySpark and Azure Data Factory for data integration and presentation, thereby enabling clear insights to stakeholders and driving actionable outcomes.Tech Stack: Azure Data Factory, Azure Databricks, SQL, Python, Power BI, Amazon QuickSight

• Collecting and interpreting data to deliver actionable insights to stakeholders across multiple domains.• Conducting data cleansing and analysis on large datasets to identify correlations and trends.• Proficient in using Python libraries such as pandas and NumPy for exploratory data analysis.• Designing and developing interactive dashboards using Power BI and Quicksight for stakeholders.• Migrating reports from Power BI to Power Apps and creating data pipelines in Quicksight for efficient data refreshes and transformations.• Utilizing DAX formulas and SQL queries for data manipulation and analysis.• Collaborating with product managers to improve user experience metrics through data-driven insights.• Implementing row-level and column-level security measures in dashboards to ensure data integrity.Tech Stack: Python (pandas, NumPy), Power BI, Quicksight, SQL, Power Apps, DAX

Being a Utility Officer, I am entrusted with the responsibility of operating all the utility systems such as Boiler, Chilling plant, RO-EDI water treatment plant & distribution system and Multi-column distillation plant and undertaking its maintenance along with my team.