Data Engineer specializing in building and optimizing data pipelines for efficient data ingestion, transformation, and analysis. Proficient in utilizing Azure Data Factory (ADF) to construct ETL pipelines for extracting invoice/contract data from SQL Server and Snowflake, and loading it into Databricks for advanced processing.Leveraged Databricks to perform complex data transformations, applying business rules and SCD logic to ensure data accuracy and consistency. Built comprehensive Power BI reports for in-depth customer agreement analysis.Embraced AI technologies like ChatGPT to streamline data transformation processes, troubleshoot complex logic, and enhance data quality. Successfully implemented ADF pipelines for extracting COPA data from SAP BW and SAP HANA, utilizing BEX queries and Databricks for efficient financial data processing.Capitalized on AI tools like Databricks Copilot and ChatGPT to accelerate development, improve code quality, and streamline financial data analysis within Databricks. Demonstrated ability to significantly reduce project costs and efforts by utilizing GitHub Copilot, ChatGPT, and Databricks Copilot to automate tasks and enhance overall efficiency.

Data Engineering & Machine Learning SpecialistWith a robust background in data engineering, machine learning, and business intelligence, I bring a wealth of experience in designing and implementing innovative data solutions across various industries. My expertise spans from genomics to sustainability, and enterprise data management.Next Generation Sequencing (NGS)Streamlined gene data through ETL pipelines leveraging Databricks and AWS.Conducted genome data modeling and exploration.Proficient in AWS services including S3, IAM, and Lambda.EDT SustainabilityCreated a dashboard to monitor energy sources.Developed a module using linear regression to normalize temperature impacts on energy usage with PySpark in Databricks.Implemented a text classification module using Facebook's FASTTEXT and NLTK for data cleansing.Recognized as an "Impact Project" at the company level.EDT Data ThreadImplemented a machine learning-driven approach for equipment mapping between Maximo and SAP.Utilized data exploration techniques and unsupervised clustering algorithms to identify patterns.Employed fuzzy matching techniques to achieve high-accuracy record matching, assisting data stewards in integration.Managed a massive dataset of over 2 billion records.I TransformationDeveloped three distinct QBR self-serve reports with custom functionality using Power BI.Automated the cataloging process with Azure Purview, Power Apps, Power Automate, and Azure SQL DB.Rationalized reports across SSRS, Tableau, and Power BI platforms.My dedication to leveraging cutting-edge technologies and methodologies to solve complex data challenges has consistently resulted in optimized processes, enhanced data accuracy, and actionable insights for stakeholders. Let's connect to explore how I can contribute to your next data-driven project!