At Google, I engineer Azure Data Factory and Microsoft Fabric pipelines, lakehouse solutions, and real-time streaming systems that improved processing efficiency by 45% and reduced reporting time by 35%.
I've built multi-terabyte data platforms across AWS and GCP using Glue, EMR, Redshift, BigQuery, Dataflow, Dataproc, Kinesis, and Pub/Sub. My work has reduced query costs, improved performance, and delivered machine learning-ready datasets, fraud detection, operational monitoring, and analytics.
I use SQL, Python, PySpark, Spark, and Databricks to optimize transformations while applying governance and security controls for GDPR, HIPAA, lineage, data quality, and enterprise privacy requirements.
