01Data Monetization Platform – Federated Data Mesh
Role: Lead Solution Engineer / Architect
Executive summary
Designed and led a proof-of-concept for a federated data mesh that lets a capital-markets client securely monetize curated market data as products—combining Fabric/OneLake domains, Databricks engineering, embedded Power BI and an AI multi-agent query layer.
- Microsoft Fabric
- OneLake
- Azure Databricks
- Power BI
- Microsoft Purview
- Entra ID
- Azure OpenAI
- NestJS
- Python
A leading capital-markets operator (a stock exchange) wanted to monetize its data assets by offering rich data products through a unified platform. Its data sat in siloed raw files with manual ETL by customers, limiting adoption. Strict regulation and multiple lines of business demanded a data-mesh architecture with domain ownership and federated governance to share data products securely with external clients.
- Architect a cross-domain data hub on Microsoft Fabric and Azure Databricks, using OneLake for unified storage and domain-specific workspaces (data mesh).
- Build data-engineering pipelines to ingest, refine and serve curated datasets (market data, trading analytics) with Spark on Fabric and Databricks.
- Add a machine-learning layer for advanced data products (trading anomaly detection, Copilot-driven insights).
- Deliver a customer-facing app: a Python multi-agent backend and a NestJS micro-frontend embedding Power BI analytics.
- Enforce governance & compliance via federated governance with Microsoft Purview, the Fabric domain model, row/column-level security and MFA for external access.
I led the architecture design with the client's data team and built a PoC on Fabric showing how OneLake and domain workspaces give each business unit isolated control while sharing data through a central marketplace. I configured Fabric medallion pipelines (Bronze/Silver/Gold) and Databricks for heavy transformations. For AI, I introduced a multi-agent approach—an Azure OpenAI agent handling user queries with Retrieval-Augmented Generation (RAG) over documentation, and another translating requests into SQL/Spark. The NestJS micro-frontend embedded interactive Power BI dashboards. I coordinated distributed teams across time zones and version-controlled designs and code.
The PoC established a robust federated data-sharing platform and demonstrated new revenue potential—securely sharing curated market data with banks and asset managers as a subscription service. It removed manual file handling and enabled near-real-time analytics on unified storage. The governance model (Fabric domains + Purview) let domain admins manage their products under central oversight, and embedded Power BI delivered a high-quality consumption experience. Stakeholder buy-in led to a defined production roadmap (landing zone, capacity planning, cost model).
Data-mesh principles can be implemented pragmatically with Fabric domains and Databricks integration. Embedding security from day one—Purview plus Entra ID—gave the client confidence in regulatory compliance. Building a multi-agent query layer underscored the need for robust orchestration to control shared state, shaping later AI agent designs.