Data Engineer with 6+ years of experience, specializing in building and managing data pipelines, architectures, and workflows across both on-premise and cloud environments, including AWS and GCP.Currently, I focus on developing robust Python-based solutions to ingest data from diverse sources using tools like Meltano and orchestrating workflows efficiently with Airflow. My expertise extends to data warehousing, where I model and optimize data using Snowflake and dbt to enhance architecture and performance.I have designed and implemented end-to-end ETL pipelines, built real-time and batch data processing systems, and worked with a variety of technologies like Spark, Scala, and Docker to streamline data processes. I’m always eager to take on new challenges and continue learning about new technologies, particularly in areas like Machine Learning and cloud-based data solutions.Key Highlights:- Data Warehouse Architect: Leading the design and development of a company-wide data warehouse using Snowflake and dbt.- ETL Pipeline Developer: Building end-to-end data pipelines using Python, Meltano, and Airflow.Workflow Orchestration: Orchestrating reliable and efficient workflows using Airflow.- AWS & GCP: Extensive experience with tools such as Big Query, S3, Redshift, and GCP Storage.Real-time Data Processing: Proficient in developing real-time processing pipelines using technologies like Kinesis and AWS Lambda.
Listed skills include Business Process Improvement, Change Management, Stakeholder Management, Itil, and 23 others.