Lokesh M

Senior Data Engineer @高盛

Built high-performance Django REST APIs in Python to streamline data retrieval and processing, improving query response times by 40% and enabling secure, real-time access to critical healthcare data.• Implemented Apache Kafka for real-time data streaming and event processing, reducing data latency from minutes to under 10 seconds and improving integration efficiency across multiple data sources.• Optimized MongoDB for scalable storage and rapid retrieval of customer-behavior data, boosting query performance by 30% and supporting faster analytics.• Designed and maintained robust Hive data models to support efficient analytics; developed end-to-end ETL pipelines with Spark SQL and PySpark to ensure data quality, reusability, compliance, and adaptability.• Deployed Docker and Kubernetes to containerize and orchestrate complex Airflow-driven data workflows, improving scalability and resource utilization.• Partnered with cross-functional teams to architect and maintain AWS-based data solutions, applying mature DevOps practices for deployment, monitoring, and automation.• Leveraged AWS, Databricks, and EMR to build cloud-native, large-scale data lake solutions, following clean-architecture principles and optimizing data ingestion pipelines.• Utilized SQL and PL/SQL to query and manage large-scale datasets in Cloud SQL and BigQuery, ensuring high performance and data integrity.• Developed interactive Tableau dashboards to visualize key healthcare metrics, empowering business stakeholders with timely, data-driven insights for strategic decision-making.