I am a Data Engineer focused on architecting scalable Data Platforms and high-performance distributed systems. My expertise lies in building the foundational infrastructure required to power Intelligent Systems, bridging the gap between massive data processing and LLMOps.
Currently, I am specializing in the Modern Data Stack, mastering distributed computing with Spark (Scala/Python) and cloud orchestration with GCP, Airflow, and Kubernetes. My objective is to design resilient data architectures that enable seamless RAG (Retrieval-Augmented Generation) and automated decision-making at scale.
- Data Infrastructure: Designing ETL/ELT pipelines and Data Lakehouse architectures using GCP and Snowflake.
- Distributed Systems: High-throughput processing with Apache Spark and real-time streaming with Kafka.
- Platform Engineering: Containerized orchestration with Docker & K8s, and Infrastructure as Code (IaC).
- AI Systems: Scalable LLMOps frameworks, Vector Databases (ChromaDB/Pinecone), and RAG integration.
| Category | Technologies |
|---|---|
| Data Engineering & Big Data |       |
| Cloud & Platform (IaC) |       |
| AI & LLMOps |      |
| Databases |        |
| Visualization & Analytics |     |
Turning petabytes of raw data into high-score insights. My contribution graph is the engine, and the code is the fuel for the next level!
MS in Big Data (UAG) • Advanced Scala • Go • MLOps (MLflow & Kubeflow) • LLM Fine-tuning • AWS Cloud Architect
