Laxmi Santhoshi Gummadavelly
Data Engineer at Cisco Systems
- Role
- Data Engineer at Cisco
- Location
- Danville, CA, US
- LinkedIn followers
- 500 followers
About Laxmi Santhoshi Gummadavelly
5+ years of experience in designing, building, and optimizing large-scale data pipelines…
Experience
Data Engineer
Jul 2024 — Present · US
Designed and deployed scalable ETL pipelines using PySpark, Airflow, and AWS Glue, automating complex ingestion, transformation, and scheduling workflows that reduced manual data processing by 45% while enabling near real-time data availability across enterprise BI and analytics platforms.Built and optimised enterprise-scale data lake architectures on AWS (S3, Redshift, EMR, Lambda), supporting 20+ business units with centralised, governed data access that improved query response times by 40% and enabled advanced self-service analytics capabilities.Implemented real-time streaming pipelines using Kafka and Kinesis to process 1M+ events per minute, ensuring sub200ms latency for IoT and customer usage data across global systems, which improved system responsiveness, scalability, and real-time decision-making.Developed Snowflake data warehouse solutions with optimized partitioning, clustering, and caching strategies, streamlining query performance and improving report generation efficiency by 30% for executive dashboards and enterprise BI reporting.Engineered dimensional data models and schemas (Star, Snowflake) in Redshift and Snowflake, applying indexing, partitioning, and clustering strategies that improved query performance and reduced storage costs by 20%, while enabling scalable analytics for enterprise users.Automated CI/CD pipelines for data workflows using Git, Jenkins, and Docker, streamlining build, test, and deployment processes that cut release times by 35% while ensuring robust version control, reliability, and traceability for all data pipeline changes.Partnered with data scientists and analysts to integrate machine learning pipelines (Spark MLlib, TensorFlow) into production, operationalizing models that enabled churn prediction with 93% accuracy and supported scalable deployment for advanced analytics use cases.Developed data validation and governance frameworks using Python, SQL, and AWS Lake Formation.
Education
Sphoorthy engineering college
Btech
Oklahoma City University
Master of Science - MS
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