Senior Data Engineer at Ernst & Young (EY)

Led enterprise data warehousing and lakehouse initiatives by building a SQL Server/SSIS-based warehouse, consolidating data from multiple sources, and delivering enterprise BI models in Power BI. Designed scalable Azure data pipelines (ADF, Databricks notebooks in Python/Scala, Synapse) to transform and load large datasets into a data warehouse. Created Data Lakes in Microsoft Fabric Lakehouse with bronze/silver/gold zones; processed data with Fabric Spark (PySpark/SQL) for real-time analytics; orchestrated ingestion via Fabric Pipelines. Optimized lakehouse performance; integrated data models with Power BI and applied Row-Level Security. Implemented data governance using Purview and AWS Glue Data Catalog. Automated CI/CD with Azure DevOps for ADF, Databricks notebooks, and Snowflake scripts.

ETL BI Engineer at Macy's, Inc

Developed batch and real-time ETL pipelines in AWS Glue and Redshift for financial analytics, processing millions of records daily. Built scalable Data Lakes on Azure Data Lake Storage and AWS S3, using PySpark and Databricks to process large datasets. Designed dimensional models and star schemas in Snowflake and Redshift to support BI dashboards. Transformed data with Python (Pandas/NumPy) and automated DBT transforms with CI/CD. Enforced data governance and access controls in Snowflake with RLS. Created Power BI dashboards to support operations, sales, and finance; integrated cross-cloud data via GCP BigQuery.