Lead Data Engineer - GCP & MLOps

Key Skills & AchievementsDesigned 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.