Ali Shahnawaz

CureMD

CureMD • Tiempo completo

Jun 2022 - Feb 2026 • 3 yrs 8 mos

• Designed and optimized real-time ETL pipelines for integrating clinical patient data into a Data Lake, storing data in Amazon S3 across Bronze, Silver, and Gold layers with automated archival for compliance and analytics. • Built high-throughput streaming solutions using Apache NiFi, Kafka, and Confluent Schema Registry, processing 4–5 GB/hour across 10–20 million records while ensuring data quality and schema governance. • Led the real-time transformation of patient data into HL7 FHIR-compliant resources using C# and Liquid templates, enabling interoperability across healthcare systems. • Collaborated with business stakeholders to implement real-time health alerts and messaging, improving longitudinal patient care and engagement. • Utilized Apache Sqoop for large-scale data migration, reducing storage overhead by 80% while maintaining database performance. • Developed PySpark jobs for patient data filtration, anomaly detection, report generation, and pipeline monitoring. • Created clinical KPI dashboards using Apache Superset and Amazon QuickSight, enabling clients to identify trends and gain actionable insights from patient data. • Implemented monitoring and alerting solutions with Grafana to ensure the reliability and stability of production data pipelines. • Designed scalable data-processing architectures supporting parallel execution across multiple healthcare practices, significantly reducing processing time. • Developed Python-based integrations with HubSpot APIs to extract, transform, and analyze marketing data, generating custom reports for campaign performance tracking.