At Honeywell, I develop and support ETL pipelines that bring data from enterprise systems into the Azure data platform. I use Python, PySpark, SQL, Azure Databricks, and Azure Data Factory to build ingestion and transformation workflows.
I work on a Delta Lake lakehouse organized into Bronze, Silver, and Gold layers. I’ve used Auto Loader for incoming files and Unity Catalog to organize data assets and manage access.
At Honeywell, I improved Spark job performance by reviewing execution plans, adjusting joins, and removing unnecessary transformations, reducing pipeline execution time by approximately 40%. I also added data validation and reconciliation checks and investigated production pipeline failures.
Previously, at Walmart, I built and maintained AWS data pipelines and supported Snowflake and Amazon Redshift reporting workloads. I also managed Apache Airflow DAGs, reducing manual operational effort by approximately 60%.
