I have earned the Google Certified Professional Cloud Architect and Data Engineer credentials, demonstrating my expertise in cloud computing and data engineering. My core competencies include big data, ETL, Spark, Python, GCP, Databricks, Data Warehouse, Data Pipelines and Azure. In my current role, I work on building data pipelines in Airflow for GCP ETL related jobs using various technologies such as Dataproc, GCS, Cloud Functions, and Big Query. I also perform data transformation and cleansing using SQL queries, Python, and PySpark, and integrate third-party applications using a microservice architecture. I have deployed the code through CI/CD pipelines and implement the best Pythonic programming practices. Previously, I worked with Microsoft's Cloud and Enterprise team as an Azure Big Data Cloud Engineer, where I developed an intelligent data-driven supply chain data platform using Azure Big Data technologies such as HDInsight, Cosmos DB, Data Factory, and Databricks. My mission is to leverage big data and cloud technologies to deliver scalable, reliable, and efficient data solutions that drive business value and innovation.