Data Pipeline Engineering
Reliable financial data pipelines that run themselves
The problem
You have financial data scattered across market feeds, bank APIs and internal systems that needs to land in one reliable, queryable place.
Most data problems in financial services are not modelling problems — they are plumbing problems. Late files, schema drift, silent gaps, and pipelines that need a human to babysit them. I build orchestrated pipelines (Dagster, Airflow) with proper observability, retries and data-quality checks so the data is correct and on time.
I have built this at scale: the data backbone at Stockopedia processing global markets, the macro pipeline behind Quantamental across 171 countries, and the ETL feeding Ansaar. The output is infrastructure your team can trust and forget about.