Aakash Madabhushi
I build the pipelines that feed dashboards and models, and the checks that keep bad data from reaching either.
A year at Sapaad building production pipelines on Databricks and PySpark: more than five million rows a day across a multi-tenant SaaS platform, feeding recommendation features and over 75 tenant dashboards. That included tuning ten or more Spark jobs for a 43% cut in p95 dashboard query latency, and a Delta Lake data quality framework whose schema and freshness checks caught 14 anomalies automatically, because those pipelines fed production ML.
The same discipline runs through my own work: an Airflow, dbt, and Snowflake medallion pipeline that reduced 27.1 million Zeek network flows into a graph a model could train on; a taxi platform built twice, once as a batch warehouse and once as a streaming pipeline with a dead-letter topic; and pre-training quality gates in my research that refuse to hand a corrupted tensor to a training run.
Every link goes to code or data you can inspect yourself.
Served the same taxi data to dashboards and to live monitoring, by building it twice: a scheduled Airflow, dbt and Snowflake warehouse joined with weather, and a Kafka path that validates trips on arrival and publishes rolling metrics.
Personal project · Nov to Dec 2025
Reached 0.711 F1 predicting flight delays across 9.5 million U.S. flights, by training a Spark MLlib random forest on 15 monthly BTS files and running it inside a Kafka stream so each incoming flight gets a probability within seconds.
SJSU big data course, team project · Dec 2025
Surfaces Wikipedia pages turning contentious in real time, by streaming every English edit through Kafka as it happens and scoring the tone of each edit summary with RoBERTa.
Personal project · Nov 2025
Keeps a full history of every revision to the data, by loading daily stock prices into Snowflake on an Airflow schedule and computing the indicators traders actually use as dbt models with snapshots.
Personal project · Oct to Nov 2025
Makes articles searchable by meaning rather than exact keywords, by embedding them with Sentence Transformers on an Airflow schedule and serving nearest-neighbour lookups from a Pinecone index.
Personal project · Nov 2025
Let each part of the system fail and recover independently, by rebuilding a Yelp-style application so services communicate through Kafka events instead of calling each other directly.
SJSU DATA 236, Distributed Systems · Spring 2026
Kept résumé parsing and embedding matching off the request path across 17 containers, by routing them through Kafka and caching profile reads in Redis for 6× faster repeat lookups, with an AI assistant that pauses for human approval.
SJSU DATA 236, Distributed Systems · Spring 2026
Reached 0.90 F1 flagging suspicious host pairs in 27.1 million Zeek flows, by condensing them into a connection graph with Airflow, dbt and Snowflake, classifying links with a graph neural network, and having Llama 3.3 explain each alert.
SJSU capstone, team project · Feb to May 2026
Select a project for the full detail and links.
I'm available from December 2026 and open to relocating. Email me and I'll reply within a day.
Hiring for something else?