Here's a README file focused on your experience as a Data Engineer, showcasing your relevant skills, accomplishments, and projects:

I am Nandini Wadaskar, a passionate Data Engineer with a strong foundation in data analytics and software development. With hands-on experience in data validation, ETL processes, data visualization, and business intelligence, I am committed to leveraging data to drive actionable insights and improve decision-making in organizations.

• Programming Languages: Python, Java, SQL
• Certifications: IBM Data Engineer
• Tools & Technologies:
  • Data Engineering: Azure Data Factory, Databricks, SparkSQL, PySpark
  • Data Visualization: Tableau, Power BI, Looker
  • Data Processing: Alteryx, SSMS, Excel, Jupyter Notebook
  • Others: Jira, Google Query, Pandas, NumPy, DAX

Mar 2024 - Present

• Data Validation and Error Rectification: Conducted comprehensive comparisons of 12 tables from two data sources, validated data types and measures, and identified and rectified errors using Alteryx and Excel.
• Tableau Dashboard Development and Data Integration: Delivered three Tableau Dashboards that provided actionable insights into pricing strategies, resulting in a 15% improvement in competitive pricing accuracy. Managed the integration of multiple data sources, ensuring seamless data flow and improving Dashboard performance.
• ETL & Data Publishing: Handled over 7 million records to a Tableau Data Source by leveraging Azure Data Factory (ADF), Databricks, and PySpark.
• Data Visualization & Reporting: Developed Power BI dashboards integrated with PowerPoint for seamless Quarterly Business Review (QBR) reporting, ensuring stakeholders had access to critical business insights.
• Tools Used: SSMS, Azure SQL, Alteryx, Tableau, Looker, Power BI, Python, Jupyter Notebook, Azure Data Factory, Databricks, SparkSQL, PySpark, Soda, Jira.

Sept 2022 – Mar 2024

• Business Intelligence and Visualization: Created interactive dashboards using SQL queries, DAX, and Power BI to visualize key business metrics, leading to an 80% improvement in data accessibility and decision-making processes. Successfully migrated dashboards from Looker to Power BI.
• Python Automation: Developed and implemented Python scripts to automate data operations, resulting in a 70% decrease in file processing time across six major projects utilizing Pandas and NumPy.
• Critical Data Analysis: Increased revenue through the implementation of pricing strategies and risk analysis, reducing customer churn and protecting profit margins by processing data from multiple inputs using SQL, Excel, and statistical analysis.
• Excel Mastery: Enhanced efficiency by developing Excel templates for rate monitoring, transit cost analysis, and competitor price comparisons.
• Pattern Analysis: Identified discrepancies in existing Power BI dashboards through in-depth pattern analysis and corrective actions.
• Azure Data Factory: Designed a data pipeline to upload files from blob storage to SSMS, ensuring seamless data integration while monitoring consistent data flow and accuracy.
• Communicating Insights within SLA: Delivered over 600 Jira tickets for cross-team functions, achieving an 86% success rate by effectively communicating and addressing root causes. Produced over 100 ad hoc reports for critical analysis across teams.
• Documentation: Developed standard operating procedures (SOPs), documented projects and scripts, and conducted departmental training.
• Tools Used: SQL Server Management Studio (SSMS), Azure SQL, Python, Jupyter Notebook, Power BI, Looker, Tableau, Power Query, Azure Data Factory, Streamlit, Google Query, PowerPivot, Excel, Google Sheets, DAX, Paginated Reports, Jira, Visual Studio Code (VS Code).

Jan 2022 - Sept 2022

• Insightful Data Handling: Leveraged Excel and Python to clean, analyze, and update HR data, providing actionable business insights.
• KPI and Metric Precision: Defined success metrics and assigned numerical values to critical business functions for streamlined comparative analysis.
• Error Management: Generated error reports and effectively managed outliers to ensure data quality and truth availability.
• Strategic Visualization: Utilized Tableau and Looker for data visualization, facilitating seamless communication with senior management.
• Tools Used: Tableau, Looker, SSMS, Excel, Power Query, Google Sheets, Google Query, Python, Scikit-learn, Matplotlib, Seaborn.

• MCA in Data Science: LPU (2024), CGPA: 8.2
• BBA in International Finance: LPU (2022), CGPA: 8.6
• 12th Grade: 86%
• 10th Grade: 94%

• Current Learning: Deepening my expertise in data warehousing, Apache Iceberg, PySpark, and advanced mathematics for engineering.
• Goals: Aspiring to become a leading expert in Data Engineering and System Design, with a long-term ambition to work at top tech firms like Google, Meta, Uber, and PayPal.

I thrive as an early riser with a structured routine, energized by small, frequent meals. A splash of cold water on my face helps me focus and stay refreshed!

• LinkedIn: Your LinkedIn Profile
• GitHub: Your GitHub Profile
• Portfolio Website: Your Portfolio (if available)

Feel free to adjust any sections or add links where necessary!