LOYALIST COLLEGE IN TORONTO, ON, CANADA
Artificial Intelligence & Data Science

Completed Post-graduation with specialization in Artificial Intelligence & Data Science at Loyalist College In Toronto, ON, Canada.

DHARMSINH DESAI UNIVERSITY
Information Technology

Completed B.Tech. Degree specialization in Information Technology at Dharmsinh Desai University, Nadiad, Gujarat, India.

The Marketing Store
Toronto, Canada.

• Technologies : Python, AWS, SQL, (CI/CD), Snowflake Cloud, DBT Cloud, Apache Airflow, Tableau, Spark, Scala, Hive, HDFS, Data Warehousing
• Builds and Re-designed ETL data models and data architecture for McDonald’s Sales, Supply Chain and Marketing data that improve accessibility, efficiency, governance, and data quality.
• Actively engaged in developing, testing, and maintaining data architectures for data platforms, Cloud databases (AWS, Snowflake), and analytical, or data science systems.
• Built and Improved ETL Automation with an advanced distributed SQL query engine for big data using AWS Athena, AWS Lambda, AWS Glue, AWS step functions, S3, AWS RDBMS, Python, Pandas, Numpy, Pytest Framework, Project Documentation, Code Review, and Analysis to Refactor and Automate old Manual ETL/ELT Data workflow.
• Developed Automation Unit testing Framework and Data validation framework.
• Working on Data-driven and event-driven architecture to build robust ETL Data systems.

Blue Valorem IT Solutions
Toronto, Canada.

• Technologies : Python, AWS, DBT Cloud, Apache Airflow, Tableau, Spark, Scala, Hive, HDFS, Data Warehousing
• Created a data pipeline to gather sales information including product, price, date, and location from multiple sources, including transactional databases and customer feedback.
• Conducted data cleansing tasks such as handling missing or inconsistent data, converting data types, and eliminating duplicates to ensure data quality for further analysis.
• Utilized Python libraries like Matplotlib and Seaborn for exploratory data analysis, employing visualizations such as line charts, scatter plots, and histograms to uncover patterns and trends in the data.
• Leveraged machine learning algorithms, regression analysis, and Decision Tree models to forecast product demand and predict future sales based on historical data.
• Developed marketing strategies by utilizing Big Data processing tools like Spark and Hive QL to analyze marketing data and provide insights for the marketing team.
• Presented actionable insights to the business through Tableau dashboards, showcasing real-time sales data, visualizations of sales trends, and future sales forecasts.
• These insights facilitated optimized inventory management, pricing strategies, and targeted marketing campaigns to maximize profitability and foster business growth.

Wholetex
Gujarat, India

• Technologies: Python, SQL, Spark, AWS, SQL, Kafka, Sqoop, Hive, Flutter - Mobile App development.
• Introduced an automated Python script that extracts data from predetermined websites, performs transformation and cleansing, and stores it in a MySQL database for production use. This initiative significantly reduced manual work by 35% and resulted in an 18% reduction in overall annual costs.
• Developed a cross-platform mobile application using the Flutter framework, resulting in increased vendor responses and surpassing the previous highest sales record by 20%.
• Leveraged Spark Streaming with Kafka to ingest a stream of data into a Hive table, making it accessible through Impala. Imported data from various remote sources, including REST API calls, LFTP, SFTP, and SSHFS, into HDFS/Hive tables for further processing and analysis.
• Utilized Sqoop to extract data from relational databases such as Oracle, DB2, and SQL Server, and loaded it into HDFS. Scheduled workflow management using Oozie and made the data available for BI reporting through MicroStrategy integration with Impala.
• Developed test scripts to support test-driven development practices and enable continuous integration for the project.

Physical Research Laboratory View Certificate
A Unit of Dept. of Space, Govt. of India , Ahmadabad.

• Developed Database of satellite images (Solar Observatory Image Dataset), cleaned it using python libraries, applied image processing on dataset, built Deep learning model for prediction of solar flares.
• Applied concepts of Hybrid Convolution Neural Network, Auto Encoder, Keras/Tensorflow, Automation tool-Selenium Web Driver, Image Processing, Jupyter Notebook and Google Colab, Python 3, gained experience related to Real Industrial Work, Team work, & Presentation Skills.