About
BMLL needed support building reliable data processing pipelines for large volumes of historical market data from over 150 global trading venues. DO OK developed Python parsers that normalised fragmented Level 1, 2 and 3 datasets into a unified structure, enabling immediate analytics and strengthening BMLL’s platform for banks, hedge funds and regulators.
Challenge, approach, and impact
Fragmented and inconsistent market data
BMLL needed to process historical data from over 150 trading venues, each using different formats, rules and structures. Normalising this volume of inconsistent data was essential for building a reliable analytics platform.
Strict accuracy and performance requirements
Financial research depends on precise, correctly harmonised datasets. Even small inconsistencies can distort analysis, so BMLL required a robust, error-resistant data processing pipeline.
Pressure to unlock data quickly
BMLL’s clients expect fast access to deep market insight. The team needed a way to accelerate data ingestion and deliver usable, high-quality datasets from day one to support time-sensitive research.
How we built
Testimonials
Backend Developer @ undefined
“Working on the BMLL project gave us the chance to solve genuinely complex data problems. We were taking raw, inconsistent market feeds and turning them into something clean, reliable and ready for analysis. It was demanding, especially with the scale of data involved, but very satisfying to see how quickly the new parsers helped unlock meaningful insight for BMLL’s clients.“
Team structure
Client team
Elliot
CPO
The client stakeholders at BMLL Technologies were working closely with the team at DO OK
Agency team
Backend Developer
Production