Experienced Data Engineer with over 4+ years of expertise in designing, optimizing, and maintaining robust data pipelines. Skilled in Python, SQL, Spark, and Power BI, and proficient in cloud platforms such as Google Cloud Platform (GCP), BigQuery, and Cloud SQL for advanced analytics and storage. I build scalable, high-performance solutions using technologies like Kubernetes, Terraform, and CI/CD tools like GitHub, Bitbucket, and Airflow for automation and streamlined deployments. With hands-on experience in Cloud Foundry and Pub/Sub, I’ve delivered cloud-native solutions that ensure data flow and integration across various environments. I strongly advocate working with GraphQL and Neo4j for efficient graph database management. I also leverage Elasticsearch for fast data retrieval and indexing in analytics workflows. I’ve used PySpark for large-scale data processing, executing complex transformations on big data. I’m adept at working with NoSQL databases like MongoDB, and my comprehensive knowledge of pipeline management enables me to optimize and deliver effective data integration solutions. My focus is on creating end-to-end, scalable architectures that drive reliable business insights while maintaining operational efficiency.