Empowering businesses with clean and reliable data solutions with over 4 years of experience in wrangling big datasets and building robust data platforms that lay the groundwork for revealing game-changing analytical insights. I conceptualized and implemented data pipelines to the stage, transforming and loading structured and semi-structured data into systems for analytics. Also, I worked as a Data Analyst in building data models for Data Reporting, Data Visualization, and gathering meaningful insights for various clients in different domains like Retail, Insurance, Mortgage & Finance. ✨ Skillset: 👉 Programming languages: Python, Scala 👉 Data processing: Spark 👉 SQL: Redshift, Azure Kusto, MySQL, T-SQL, Athena 👉 Storage Files: Parquet, CSV, JSON, Excel 👉 Reporting: Power BI, Tableau 👉 Cloud providers: AWS, Azure 👉 ETL Tools: Databricks, Azure Synapse Analytics, Azure Data Factory, AWS Glue, Snowflake. 🛞 Serverless: AWS Lambda, Azure Functions ⚓ File Storage: AWS S3, Azure Data Lake Gen2 🫧 Core Competencies: 👉Data Warehousing 👉Designing ETL Pipeline Architecture 👉Data Modeling 👉Database Migration 👉Business Intelligence 👉Database Design 👉Strategic Planning and Implementation 🌟 Achievements: 👉Maintained data pipeline up-time of 95% while ingesting streaming and transactional data across 7 primary data sources. 👉Automated ETL processes across millions of rows of data, which reduced manual workload by 30% weekly. 👉Optimized ongoing process of data transformations in Spark reducing execution time by 65% using best-distributed computing practices. 👉Received positive client testimonies from Mortgage and Finance domains. 📧 Feel free to reach me at prashantwitty@gmail.com to discuss any data-related solutions.