Data architecture and governance
Schema design, data contracts, reference data, lineage, dataset versioning and vendor integration.
Data architecture · Quantitative finance
Reliable data foundations for research and trading.
I am a data architect and senior Python engineer working at the intersection of market data, quantitative research and production trading. I design scalable data systems, shared models and engineering standards that make high-volume financial data reliable, reproducible and useful.
Expertise
Architecture through production
Hands-on delivery across governance, software, infrastructure and data-intensive financial systems.
Market-data platforms
Tick, trade, quote, reference and on-chain data serving research, execution and operations.
Distributed data engineering
High-volume ingestion and compute using Python, Rust, Apache Arrow, Dask, Ray and cloud storage.
Research and ML infrastructure
Reproducible datasets, GPU-enabled research environments, experiment tracking and productionisation.
Selected impact
Systems built at production scale
Designed and deployed high-volume Rust pipelines handling approximately 160 billion rows.
Optimised core Python pipelines and removed processing bottlenecks affecting research and trading.
Built a shared service providing consistent instrument and asset identities across venues.
Introduced point-in-time correctness, versioning and lineage so results can be reconstructed reliably.
Technology
Core toolkit
A practical stack organised around the systems I design and operate.
Languages & APIs
- Python
- Rust
- SQL
- gRPC
- FastAPI
Data & compute
- Apache Arrow
- Dask
- Ray
- ClickHouse
- S3 data lakes
Cloud & platform
- AWS
- GCP
- Docker
- Kubernetes
- CI/CD
Research infrastructure
- Distributed compute
- GPU workloads
- Experiment tracking
- ML infrastructure