• Built scalable data pipelines using SQL and PySpark, reducing processing times by 35% while maintaining 99.5% accuracy.• Collaborated on Azure-based solutions, enhancing data ingestion and validation processes, contributing to a 50% reduction in data discrepancies.• Optimized ETL workflows using Azure Synapse and Databricks, reducing data processing times by 35%.• Implemented advanced DAX queries to improve reporting accuracy by 30%, delivering actionable insights for operations.• Developed 15+ Power BI dashboards, enhancing data accessibility by 45% and decision-making speed by 30%.• Worked closely with analytics and operational teams to deliver timely insights, contributing to continuous improvement in data-driven processes.• Migrated legacy dataflows to SQL Server, improving data governance and reducing discrepancies by 40%.• Conducted data cleaning and transformation for structured and unstructured datasets, ensuring seamless integration across projects.• Utilized DAX queries to streamline reporting processes, reducing report generation time by 15%.• Collaborated with cross-functional teams to support continuous process improvements, leading to a 50% reduction in data discrepancies and errors.• Liaised with finance and IT teams to determine optimal data delivery methods, enhancing cross-functional communication and alignment with project objectives.• Conducted data cleaning and transformation using PySpark, ensuring consistency and accuracy in structured and unstructured data sources.• Built scalable SQL and PySpark pipelines, improving data processing efficiency by 35%.

• Leveraged Excel and Exploratory Data Analysis (EDA) techniques to cleanse data, generate actionable insights, enhancing the stability of information for strategic decision-making.• Developed SQL-based reports on time tracking and financial metrics, enabling senior leadership to make informed decisions.• Built real-time KPI dashboards, optimizing data visibility and improving response times for operational issues by 25%.• Worked with cross-functional teams to validate data accuracy and deliver reporting aligned with business goals.• Conducted data extraction automation with Python, reducing report generation time by 20% and ensuring data integrity across sources.• Skillfully diagnosed and resolved SQL Database Queries, optimized queries, risk issues, ensuring precise data extraction and manipulation, critical for maintaining data integrity and accuracy.• Performed business validation and KPI analysis using Python, SQL, Excel to optimize business operations and helped increase On-Time-Delivery (OTD) by 18%.• Led a team to analyze customer behavior and preferences also working on application development, resulting in a 15% increase in customer engagement and revenue generation.• Identified customer behavior patterns using statistical analysis and machine learning techniques, and forecast churn risk by synthesize large data, resulting in a 30% decrease in churn rate.• Developed Power BI reports with live data extraction, optimizing data integrity, and implemented data refresh schedules, resulting in a 25% efficiency gain.

• Implemented network automation tools to reduce downtime by 15%, integrating AI/ML algorithms to predict outages.• Worked closely with telecommunications clients to optimize networking solutions, using Netcool and ServiceNow for incident management.• Managed day-to-day operations of production network systems, improving system availability and fault tolerance.• Managed project workflows, incorporating Jira and Confluence to ensure smooth collaboration and resolve 10+ operational issues.• Created and maintained documentation for data workflows, improved process efficiency by 15%.• Led data analysis projects to enhance transportation processes, using Excel and SQL to monitor network capacity and courier performance, achieving a 12% increase in efficiency.• Conducted ad hoc data analysis and created visualizations using Tableau and Python, delivering actionable insights to stakeholders, resulted in a 20% improvement in network device performance.• Spearheaded the automation of KPI monitoring systems, using SQL to track key performance indicators for network reliability, reducing troubleshooting time by 30%.• Managed project workflows, incorporating Jira and Confluence to ensure smooth collaboration and resolve 10+ operational issues.• Created and maintained documentation for data workflows, improved process efficiency by 15%.

• Executed system testing on Bluetooth Classic (BR/EDR) and Bluetooth Low Energy (LE) for Intel Bluetooth Adapter.• Facilitated the identification of more than 35 new product bugs and software issues through collaboration with cross-functional teams.• Led the validation and testing of a large-scale Wi-Fi network, utilizing data analysis techniques to assess network performance and identify areas for improvement.• Generated insightful reports and visualizations to effectively communicate findings to stakeholders, resulting in the resolution of around 10 product bugs and an overall enhancement in performance.• Applied different kinds of testing like ad-hoc system-level testing, sanity, smoke and black box testing• Performed Functional, IOP, and Sanity test cases for the weekly build releases

Proficient in SQL, Linux, and C programming languages: Internship has given me hands-on experience in these key technical skills, which can be valuable in a data analyst role.Developed expertise in data analysis and data science: Through the internship, I gained experience in data analysis and data science, which can demonstrate my ability to work with complex data sets and derive insights from them.Applied knowledge in a real-world setting: The internship allowed me to apply my technical and analytical skills to real-world scenarios, giving me valuable experience that can translate to success in the data analytics field.