Darsshan Sondagar

Experience

• 

  Adani Group

  Jul 2019 - Apr 2021

  Data Analyst

  Crafted custom Python scripts for in-depth data analysis, uncovering patterns, trends, and anomalies.Utilized Python with pandas and NumPy for data analysis, cleansing, and manipulation, revealing actionable insights.Created interactive visualizations with Matplotlib and Seaborn to convey complex findings clearly.Established and automated data pipelines for scheduled data loading into Snowflake.Employed SQL for complex data transformations, including pivot/unpivot and recursive queries, converting 10TB+ of raw data into insights.Optimized ETL processes using parallel processing and data partitioning, reducing processing time by 60% and increasing efficiency by 40%.Used Cosmos DB APIs (SQL, MongoDB, Graph) to access and manipulate data as needed.Refined ETL pipelines to ensure timely, high-quality data availability, optimizing workflows and scalability.Conducted Oracle database performance analysis with Oracle Enterprise Manager, reducing query times by 40% and improving responsiveness by 25%.Developed 50+ interactive Tableau dashboards for real-time KPI insights, aiding 30 stakeholders and enhancing turnover and fulfillment rates.Implemented AWS Glue for data integration and ETL, reducing processing times by 40% and enabling timely insights.Automated file transfers and validation processes, ensuring high-quality data availability for analysis.Leveraged SAP HANA for real-time analytics, boosting decision-making agility.Built robust data pipelines with Apache Kafka, enhancing data streaming and accessibility.Utilized Oracle BI tools to analyze sales performance, driving informed decision-making and business growth. Show less

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  Capgemini

  May 2021 - Jul 2022

  Data Analyst

  • Developed and maintained complex SQL queries to extract, transform, and analyze large datasets from PostgreSQL databases, ensuring data accuracy and integrity for reporting and analysis.• Leveraged Python to create automated data processing scripts, implement statistical models, and conduct advanced data analysis tasks, improving the accuracy and efficiency of forecasts by processing up to 50 records per hour.• Deployed and managed data solutions using Azure services such as Azure Data Factory and Azure SQL Database, enhancing data integration processes and ensuring seamless data flow across the organization.• Developed and published 15+ interactive dashboards and reports in Tableau, transforming complex data sets into easily understandable visualizations that facilitated data-driven decision-making among stakeholders.• Created dynamic dashboards in Excel using slicers and interactive charts, providing real-time insights and enabling stakeholders to drill down into specific data points.• Applied text mining techniques to unstructured data sources, extracting valuable insights and patterns to support decision-making and assessment processes.• Conducted detailed risk analysis, utilizing statistical techniques to identify potential risks and provide actionable insights to mitigate them, analyzing risk factors for various products and scenarios. Show less

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  McKesson

  Jan 2024 - May 2024

  Data Analyst

  Gathered requirements and collaborated with management to prioritize business needs, creating detailed design documents.Utilized SQL queries and Advanced Excel for data preparation and analysis, including data collection, cleaning, filtering, mining, statistical modeling, and visualization.Worked with RDBMS databases like MySQL and MS SQL Server, handling structured data in CSV and Excel formats.Employed tools such as DAX, VBA (macros), VLOOKUP, XLOOKUP, Power View, Power Map, Heat Map, pivot tables/charts, and PowerPivot to enhance healthcare service delivery and patient outcomes at McKesson.Performed data preparation, fetching, profiling, mining, and visualization using Python (NumPy, Pandas, SciPy, Scikit-learn) in the Anaconda Jupyter notebook platform.Imported real-time data into Hadoop using Kafka and Spark Streaming.Extracted data from DB2, SQL Server, Oracle, and Netezza databases.Engineered automation solutions using Spark SQL and PySpark for healthcare data management, reducing manual entry by 300+ hours annually and improving efficiency and accuracy.Collaborated with healthcare providers at McKesson to create personalized BI dashboards for monitoring health trends across 1,000+ patients, improving data-driven insights by 25%.Automated reporting functions using Power BI tools, integrating with MySQL and Data Warehouse sources.Designed and developed Power BI dashboards with various chart types, including Pie Charts, Bar Charts, Tree Maps, Circle Views, Line Charts, and Scatter Plots.Created interactive Power BI dashboards aligned with business requirements for dynamic insights.Developed and maintained a robust data governance framework at McKesson, ensuring compliance with healthcare regulations and improving data quality and reliability by 25%. Show less

• 

  Blue Cross Blue Shield of Texas

  Jul 2024 - now

  Data Analyst

  • Data Pipeline Development and Maintenance: Successfully developed and maintained complex data pipelines using Python, SQL, AWS technologies, and Excel to extract, transform, and load (ETL) large datasets from various sources into a centralized data warehouse, enabling efficient and effective data analysis.• Agile Methodology: Employed Agile methodologies to ensure efficient project delivery, adaptability to changing requirements, and continuous improvement in data analysis processes.• Cross-Functional Collaboration: Collaborated effectively with cross-functional teams (e.g., actuarial, clinical, marketing), resulting in the translation of complex data insights into actionable recommendations that directly impacted healthcare processes and outcomes.• Data Visualization and Reporting: Developed and maintained interactive data dashboards using Power BI, and Excel to provide stakeholders with real-time insights into key performance indicators and driving data-driven decision-making.• Predictive Modelling: Implemented machine learning models (random forest, logistic regression) to accurately predict patient outcomes, healthcare costs, and identify high-risk populations, contributing to improved healthcare decision-making.• Mentorship and Innovation: Provided technical guidance and mentorship to junior data analysts, fostering a culture of data-driven innovation and continuous improvement within the team. Show less