Real products, not demos.

I’m a computer-science student in Visakhapatnam who would rather ship a working system than a slide about one. Over the last year that has meant end-to-end data pipelines — change-data-capture from PostgreSQL through Debezium and Kafka into Spark Structured Streaming, batch ETL into star-schema warehouses with SCD Type 2 history, data-quality gates, Airflow orchestration and idempotent, observable jobs.

It has also meant products: authentication, REST APIs, relational data models and polished front-ends — increasingly with AI at the core, from a LangGraph multi-agent operations layer with a human-in-the-loop safety gate to KYC and document forensics that run entirely on-device with ONNX and WASM.

Ask me about Spark internals (lazy evaluation, shuffles, broadcast joins, foreachBatch, checkpoints), Kafka and CDC semantics, dimensional modelling, data-quality strategy, SQL window functions, Next.js and React architecture, or shipping LLM features to production — RAG, agents, evals.

Currently exploring Databricks & Delta Lake, Snowflake, Hadoop / Hive, Kafka Streams and Data contracts. Fundamentals I keep sharp: data structures and algorithms, OOP, DBMS, operating systems, computer networks and system design.