I build end-to-end data pipelines and analytical systems using Python and SQL, with a focus on data modeling and orchestration.

I particularly enjoy working on analytics pipelines and tools around things I feel drawn to, viz. cricket, music, and memories, mainly.

End-to-end ELT data pipeline for ball-by-ball cricket match data using Python, PostgreSQL, dbt, and Airflow.

• Incremental ingestion & loading
• Layered warehouse modeling
• Fully orchestrated transformations via Airflow (Astronomer Cosmos)

🔗 Repo: https://github.com/shsiddhant/cricket-warehouse

A web application for exploring music listening history from Last.fm and Spotify.

Instead of focusing only on aggregate stats, it surfaces long-term and local patterns such as attachment, repetition, and obsessive listening, to help you revisit periods of your life through music.

🔗 Live: https://memory-fm.vercel.app
🔗 Repo: https://github.com/shsiddhant/memory.fm

Recent Tracks

∙ Love Minus Zero / No Limit (Live) - Bob Dylan
∙ If You See Her, Say Hello - Bob Dylan
∙ 'Til I Fell In Love With You - Bob Dylan

Projects built while learning and exploring ideas around data, memory, and interfaces:

• memory.text: Reimagine your chat history into a book-like reading experience (Qt/Pyside).
• Women’s Cricket WC: Predict match outcomes using features engineered from historical match data.
• memory.journal: Offline journaling application with password protection and Markdown support.

• Data & Backend: Python • SQL • PostgreSQL • dbt • Airflow • FastAPI • Flask

• Analytics & ML: Pandas • NumPy • Scikit-learn

• Interfaces & Applications: React • PySide6

• Infrastructure & Deployment: Docker • Supabase • Render • Vercel

• Data engineering & pipeline design
• Analytical modeling & data products
• Sports analytics (especially cricket)
• Personal data systems (music, memory, journaling)

If something I build strikes a chord with you, please consider supporting me. Thank you!