Bridging the gap between raw data and actionable AI at scale. Specializing in high-throughput data architectures and production-grade ML systems (MLOps).
I don't just write code; I design ecosystems. My work sits at the intersection of Scalable Data Engineering and Applied Artificial Intelligence.
- Google Cloud Professional Data Engineer (Expertise in BigQuery, Dataflow, and Dataproc)
- Google Cloud Professional Machine Learning Engineer (Expertise in Vertex AI, TFX, and Model Governance)
| Data Engineering | AI & Deep Learning | MLOps & Infrastructure |
|---|---|---|
| Real-time Streaming: Pub/Sub, Kafka | LLM Orchestration: LangChain, LlamaIndex | Orchestration: Kubernetes (GKE), Airflow |
| Warehouse/Lake: BigQuery, dbt, Spark | Frameworks: TensorFlow, PyTorch, JAX | IAC: Terraform, Pulumi, Helm |
| ETL/ELT: Apache Beam, Dataflow | GenAI: Vertex AI, OpenAI, HuggingFace | CI/CD: GitHub Actions, ArgoCD, Kubeflow |
I'm always looking to contribute to Research Collaborations, Cloud-Native Data Architectures, and Enterprise AI Solutions.
- 💬 Ask me about: GCP Architecture, ML Pipelines, and Data Scaling.
- ⚡ Fun Fact: I believe if it's not automated, it's a technical debt.

