I'm a data engineer with 5+ years of experience building and maintaining robust data pipelines. I thrive in environments where I can leverage my technical skills to transform raw data into actionable insights. I'm proficient in various tools and technologies, including Python, SQL, cloud platforms such as AWS, and Databricks, and data warehousing solutions such as Redshift, and Snowflake. My experience spans across the entire data lifecycle, from data ingestion with tools like AWS Glue to data transformation using Spark and data modeling with techniques like dimensional modeling. I'm also well-versed in building scalable data architectures on cloud platforms to ensure efficient and cost-effective data management.Additionally, I leverage my expertise in ETL/ELT methodologies to automate data movement and transformation processes. I'm proficient in data visualization tools such as Tableau, and Power BI to create clear and insightful dashboards and reports for better decision-making. My experience also extends to workflow orchestration tools like Apache Airflow for building reliable and scalable data pipelines that ensure timely and accurate data delivery. I am well equipped with knowledge of Generative AI, Prompt Engineering, Retrieval Augmented Generation (RAG), and LlamaIndex to build data-driven applications using a Large Language Model (LLM).Beyond the technical expertise, I possess a strong analytical mind and a collaborative spirit. I enjoy working closely with data analysts, data scientists, and business stakeholders to understand their needs and translate them into efficient data solutions. I'm constantly seeking new challenges to learn and adapt to the ever-evolving data landscape.