Saloni Mourya

Automated recurring Sales and Marketing reports in Microsoft Fabric using SQL and Power Query transformations on organization-wide Sales and Marketing datasets, reducing manual reporting effort and improving consistency Built and maintained SQL-based data models across Fabric Dataflows and Lakehouse layers to deliver clean, reliable datasets for analytics and reporting use cases Created semantic models and KPI datasets supporting Power BI dashboards, enabling teams to monitor performance metrics and business trends on scheduled refreshes

Business Intelligence Specialist - CSL Berkshire Operating Company LLC (Clearwater Living) - Irvine, CA

(2025-10)

• Automated recurring Sales and Marketing reports in Microsoft Fabric using SQL and Power Query transformations on organization-wide Sales and Marketing datasets, reducing manual reporting effort and improving consistency
• Built and maintained SQL-based data models across Fabric Dataflows and Lakehouse layers to deliver clean, reliable datasets for analytics and reporting use cases
• Created semantic models and KPI datasets supporting Power BI dashboards, enabling teams to monitor performance metrics and business trends on scheduled refreshes
• Translated business reporting requirements into production-ready BI solutions with governed datasets and dashboards

Application Development Analyst - Accenture - Pune, India

(2022-12 - 2023-07)

• Engineered scalable ETL workflows by integrating AWS services (Lambda, S3, RDS) with Snowflake, reducing overall data ingestion and processing time by 40%
• Applied clustering and regression analysis to inform business decisions and forecast trends, driving strategic insights
• Developed TensorFlow-based machine learning models to predict user errors, enhancing prediction accuracy by 15%
• Applied statistical time-series techniques (ARIMA, Exponential Smoothing) for data-driven financial insights

Application Development Associate - Accenture - Pune, India

(2021-10 - 2022-11)

• Developed Python scripts to process raw datasets from SQL databases, enabling faster data preparation for predictive modeling
• Automated the collection of data from over 150 sources, streamlining workflows and reducing manual efforts by 30%
• Applied regression techniques to identify key trends in operational data, improving forecasting accuracy by 10% and supporting data-driven decision-making for clients
• Diagnosed and resolved data inconsistencies in complex datasets through effective debugging, reducing bug resolution time
• Supported data visualization efforts using Tableau to create interactive dashboards for stakeholders, enhancing the accessibility of business insights and reducing report turnaround by 25%

Master of Science - Information Technology - Arizona State University (2023-08 - 2025-05)

Bachelor of Technology - Computer Science and Engineering - Rajiv Gandhi Proudyogiki Vishwavidyalaya (2017-08 - 2021-06)