Sahil Gawande

About Sahil Gawande

Data Engineer with 5+ years of experience designing and optimizing data pipelines, data…

Experience

1. Data Engineer with Ai Ml Integration

   Cisco

   Feb 2024 — Present · US

   Designed and deployed ETL pipelines with Apache Spark, DBT, and Airflow to ingest multi-terabyte ERP, CRM, and IoT datasets into Snowflake, reducing refresh cycles from 12 hours to 1 hour and improving reporting accuracy by 40%. • Developed Databricks workflows for advanced transformations and ML feature engineering, enabling near real-time analytics and reducing model training time by 35% through optimized data preparation pipelines. • Integrated LLMs (ChatGPT, Claude) into data validation and documentation pipelines, automating data quality checks, anomaly explanations, and metadata documentation, saving ~20 analyst hours per week. • Built real-time Kafka pipelines integrated with Spark Streaming to process 2M+ daily transactions, enabling anomaly detection systems to respond 25% faster to security threats through low-latency data processing. • Optimized Snowflake warehouse performance by applying clustering, caching, and schema redesign, reducing query runtimes by 30% and lowering compute costs by 22% while improving scalability for analytics workloads. • Partnered with data scientists to embed ML models into production pipelines using Databricks MLflow, enabling predictive network monitoring that reduced system downtime by 15% and improved service reliability. • Implemented CI/CD pipelines using Jenkins, Git, and Docker for automated testing and deployment of data workflows, ensuring 90%+ deployment success rate and reducing release cycles from weeks to days. • Ensured HIPAA, GDPR, and SOX compliance by embedding role-based access controls, audit logging, and encryption into ETL workflows and cloud data pipelines, strengthening data security and regulatory adherenc. • Delivered executive dashboards in Power BI and Tableau showcasing AI-driven KPIs for fraud detection, patient analytics, and operational efficiency, reducing manual reporting by 35% and enabling faster data-driven decisions.