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ML Engineer in the making. Building end-to-end AI solutions from data pipelines to deployment. Always experimenting, always improving.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
sec-filing-rag-pipeline
June 29, 2026 – Present
sec-filing-rag-pipeline — GitHub repository
View Projectfoodlens-data-engineering
April 10, 2026 – Present
foodlens-data-engineering — GitHub repository
View ProjectReal-Time-Stock-Market-Pipeline
March 4, 2026 – Present
A production-style data engineering pipeline that ingests live stock market data, streams it through Apache Kafka, processes it in Databricks using PySpark Structured Streaming, stores it in a Delta Lake medallion architecture, transforms it with dbt, and orchestrates the entire workflow with Apache Airflow.
View ProjectCultural Fit Analysis
The candidate's personal projects indicate a self-starter attitude and a passion for learning new technologies. The diversity of projects, from RAG pipelines to real-time data engineering, suggests adaptability. However, the lack of professional experience or team-based projects makes it difficult to fully assess cultural fit in a collaborative work environment.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback provided.