🚀 A data engineering and analytics professional with a strong foundation in data architecture, data modeling, system design, machine learning and deep learning, currently focused on unlocking the potential of Generative AI, Agentic systems and expanding that toolkit to build intelligent, autonomous solutions with GenAI.

• 📐 AI Explorer: With practical knowledge of CNNs, RNNs, supervised & unsupervised learning, and core statistical concepts, I’m transitioning into advanced GenAI territory with structured self-learning.
• 🚦 Methodical Learner: My approach blends disciplined study with hands-on experimentation, always aligning with tangible project outcomes and scalable architecture.
• 📦 Portfolio Architect: I’m developing high-impact demos and project templates that showcase the synergy of engineering, AI, and real-world functionality.

• Languages: Python(primary), SQL, Bash, C++
• Frameworks & Libraries: FastAPI, PySpark, Pydantic, Docker
• AI & ML: Scikit-learn, TensorFlow (basics), PyTorch (basics), CNN/RNN fundamentals
• Data Warehouse: Open Lakehouses, Databricks, Snowflake
• Version Control: Git, Bitbucket
• Cloud Platforms: AWS, GCP. Azure Databricks
• Database: PostGRE, MySQL, MongoDB
• Distributed Systems: Hadoop, Hive, Presto, Apache Kafka, Apache Flink, Apache Spark, Dremio, Trino
• System Design: Event-driven architectures, modular deployment, API-first design

• DeepLearning.ai Data Engineering Certificate
• AWS Solution Architect Associate
• Databricks Data Engineer Associate
• Calculus for Machine Learning
• Databricks GenAI Fundamentals

• 💼 LinkedIn: Your LinkedIn
• 🌐 Portfolio: [Coming soon]

"Engineering clarity from complexity. Building AI systems with purpose." ✨