Data engineering & analytics
From transaction logs to decisions.
We build the pipelines between operational systems and the people who analyse them: ETL, lake storage, surveillance datasets and model-serving APIs.
Signs you need this
- Business dashboards depend on manual extracts.
- Compliance or surveillance teams need daily audit data they can query.
- Your data scientists have a model, but no production API around it.
- Storage costs grow faster than the value of the data.
What we do
ETL pipelines
Extraction from transactional systems into Parquet on S3, exposed through Athena to Power BI and other tools.
Surveillance and audit datasets
Daily collection from SFTP and vendor feeds, then transformation and storage for trading surveillance teams.
Model APIs
Pricing and margin models served behind secured APIs, with FastAPI, MLflow and Okta.
Scheduling and reliability
Hangfire jobs, retries, alerting and data quality checks.
What you get
- Production pipelines with monitoring
- Documented data contracts
- Query-ready tables and views
- A versioned model API
Related work
Audit and fills data for trading surveillance
A daily pipeline that gives the trading surveillance team queryable audit and fills data from Trading Technologies.
Read the case studyReal-time pricing and analytics for an energy sales desk
Features across three integrated trading applications: real-time price negotiation, trader and sales blotters, analytics and a margin prediction API.
Read the case studyQuestions
Do you replace our data platform?
Rarely. We usually add pipelines and datasets to the platform you already run, whether that is AWS, Azure or on-premises SQL Server.
Can you work with our data scientists?
Yes. They own the model; we build the API, the versioning and the deployment around it.