Key Skills & Achievements

- Designed and implemented a customized Data Pipeline Framework using GCP Dataflow and Apache Beam.
- Delivered multiple AI/ML solutions on Google Cloud Platform (GCP) across various business domains.
- Implemented DevOps and MLOps practices for end-to-end automation, monitoring, and governance of data pipelines and machine learning systems.
- Led MIG implementation for a Reconciliation Dashboard solution.
- Developed a Dataflow Flex Template Framework and domain-specific Python libraries to accelerate data engineering workflows.
- Built and automated Kubeflow Pipelines for streamlined ML model training and deployment.
- Applied DevOps best practices to ML systems, ensuring scalability, reliability, and continuous delivery.
- Automated continuous deployment of Django applications on GCP.
- Implemented and automated Cloud Run deployments and serverless application management.




- Configured Google Secret Manager and Cloud KMS with deterministic encryption for secure data processing.
- Developed automated CI/CD workflows using Google Cloud Build.
- Performed BigQuery data extraction, preprocessing, and automated job execution for large-scale analytics workloads.
- Managed model lifecycle and maintenance using GCP Model Registry.
- Developed microservices and REST APIs for scalable cloud-native applications.
- Built customized web applications for AI Platform resource provisioning, orchestration, and management.
- Implemented automated continuous deployment pipelines for Google Cloud Functions.
- Deployed and managed analytics dashboards using R Shiny and Python Django.
- Optimized application code, cloud resources, and deployment processes to improve performance, maintainability, and operational efficiency.

📌 Lead Data Engineer - GCP & MLOps (Sydney)
🏢 N2S.Global
📍 Sydney