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Vandan Raval is listed as Seeking Internships | MS in Business Analytics & Artificial Intelligence at University of Texas at Dallas | Data Engineer & Data Analytics | Python | Hadoop | SQL | AWS | Azure | Tableau based in Dallas, Texas, United States. AeroLeads shows a matched LinkedIn profile for Vandan Raval.
Vandan Raval previously worked as Data Engineer (Student Consultant) at Conagra Brands and Data Engineer at Mobisium. Vandan Raval holds Masters In Business Analytics from The University Of Texas At Dallas.
As an individual, I have always been captivated by the power of data and its potential to be transformed into meaningful patterns and insights. My fascination with this field took root during my undergraduate in Computer Engineering program at the University of Mumbai. Courses such as 'Data Warehouse and Mining' and 'Applied Machine Learning' provided me with a robust foundation in concepts spanning business data warehousing, clustering, data visualization, regression, and both supervised and unsupervised learning.Currently, I am immersed in pursuing a Masters in Business Analytics at the University of Texas at Dallas, where I am expanding my knowledge base. This experience is a pivotal step forward in fueling my passion for data engineering and solidifying my commitment to a career in this domain. As an aspiring data engineer, I thrive on bridging connections - whether it's linking concepts across various fields, uniting individuals from diverse teams, or integrating solutions from different industries. Knowledge area: Data Engineering, Data Analysis, Data Visualization, Statistical Modeling, Predictive Analytics.Proficiencies in: Python, SQL, R, JavaScript, AWS, Azure Data Factory, Hadoop, Zookeeper, Apache Spark, Apache Kafka, Tableau, Power BIPlease feel free to connect or reach out:Email: vandan.raval@utdallas.edu | vandan.t.raval@gmail.com
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Dallas, Texas, United States
Built scalable ETL pipelines using Python and AWS Redshift, optimizing data flow and enabling real-time insights from large sales datasets.Optimized AWS Athena queries and data models, performing A/B testing to validate KPIs and presenting actionable insights to stakeholders.Automated data workflows and leveraged predictive modeling to identify 2 new product opportunities, enhancing market strategies and collaboration.
Mumbai, Maharashtra, India
•Developed scalable data pipelines for the Content Marketplace Platform using AWS Glue, Lambda, and Kinesis, enhancing data retrieval speeds by 20% for 10,000+ content writer profiles.•Designed a data schema with Mongoose, enforced MongoDB validation, and integrated using AWS Lambda, achieving a 25% increase in scalability for 15,000+ users.•Automated data validation and transformation processes using AWS Glue and Python, reducing manual errors by 42%.•Leveraged Amazon QuickSight for real-time data insights, utilizing its user-based pricing model and integrating custom APIs resulting in cost reduction. •Collaborated with data analysts and content writers to troubleshoot data pipeline issues and improve data flow.
Mumbai, Maharashtra, India
• Developed and automated ETL processes using AWS Glue and Python, for streamlining data ingestion and transformation reducing data processing time by 30%.• Loaded over 1 million records into Amazon S3 buckets and utilized AWS Lambda for seamless data transfers to MySQL databases, reducing data retrieval time by 25%.• Developed Power BI dashboards for real-time insights into course sales trends, enhancing marketing decision-making efficiency by 15%.
I graduated with a Bachelor's degree in Computer Science Engineering from VIVA Institute of Technology, Mumbai University in the year.
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Vandan Raval is listed as Seeking Internships | MS in Business Analytics & Artificial Intelligence at University of Texas at Dallas | Data Engineer & Data Analytics | Python | Hadoop | SQL | AWS | Azure | Tableau.
Vandan Raval is based in Dallas, Texas, United States.
Vandan Raval has worked for Conagra Brands, Mobisium, and Stat Institute.
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Vandan Raval holds Masters In Business Analytics from The University Of Texas At Dallas.
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