With over eight years of experience in a rapidly evolving IT landscape, I've specialized in Data Engineering and Big Data, particularly utilizing cloud technologies such as AWS and Azure. I have consistently driven projects toward enhanced efficiency, scalability, and performance. I have developed a deep proficiency in SQL, Python, and Scala, enabling me to build sophisticated data processing and automation solutions across leading cloud platforms like AWS, Azure, and GCP. Utilizing a broad spectrum of services (including EC2, S3, RDS, EMR, DynamoDB, Redshift, Lambda Blob Storage, Data Lake, and Databricks Data Factory, (GCP) services, including Big Query, Google Cloud Composer, Cloud Dataflow, Cloud SQL, Cloud Bigtable, Firestore, Deployment Manager, Google Kubernetes Engine ) to architect and deploy scalable cloud solutions.I have experience with big data technologies such as Hadoop and Spark and tools like Kafka, Hive, Pig, and HBase, which allow for efficient data storage, processing, and analytics at scale.I have effectively implemented and optimized solutions using Amazon Redshift, Azure SQL Data Warehouse, and Snowflake, enhancing data storage and retrieval efficiency. My work with ETL tools, including Informatica PowerCenter and Talend, has supported complex data extraction, transformation, and loading processes, furthering data integration and accessibility.I use data visualization tools like Power BI and Tableau for insightful analytics and decision support. Additionally, my explorations into machine learning have opened new avenues for predictive analytics and advanced data-driven strategies.