Industry Domains: Production •  Industrial IoT (IIoT) & Digital Twins • RegTech & GxP Compliance  

End-to-End Microsoft Fabric solution with Git Documentation

Tech Stack & Architecture: Microsoft Fabric (OneLake, PySpark, SQL Endpoint), Power BI (Direct Lake & Import Mode Production, DirectQuery Prototype), Medallion Architecture (Star Schema).

Architectural Rationale: The platform was initially prototyped in DirectQuery to evaluate real-time telemetry potential. For the production suite, I transitioned to a high-performance Direct Lake / Import hybrid. This strategic move leverages the VertiPaq in-memory engine to ensure sub-second interactivity for complex ESG and financial DAX measures, effectively bypassing the traditional trade-off between data freshness and analytical performance.

Strategic Impact:

• Business Value: Identified 81,744 MWh in recorded efficiency risk, translating technical grid waste into €4,904,640 of avoidable costs.

• Operational Excellence: Engineered a "Single Source of Truth" maintaining 102.59% heat self-sufficiency while tracking ESG targets across a diverse energy fleet.

• Core Skills: PySpark, SQL, DAX, Fabric ETL, Medallion Architecture, CI/CD with Git Documentation.

BIP HMI Dashboard - Anomally detection

Transforming Telemetry into Autonomous Intelligence 

In high-stakes biomanufacturing, telemetry data is often siloed in static logs, leading to a reactive operational posture where deviations are discovered only post-batch. This gap creates significant risk for high-value pharmaceutical yields.

I developed the Bioprocess Insight Platform (BIP): a containerized, AI-augmented Triad Microservice Architecture designed to serve as a high-fidelity Digital Twin for Sartorius Biostat® fermentation systems. Unlike a simple dashboard, BIP orchestrates three independent Dockerized layers to provide a closed-loop, compliant solution: 

• Autonomous SCADA Simulation (AI Pilot): A high-frequency FastAPI engine that streams multivariate sensor data and features an integrated AI Pilot. This layer monitors batch health in real-time and automatically triggers corrective Impeller RPM adjustments to restore Dissolved Oxygen levels via physics-based coupling.

• GxP Compliance & Governance: A dedicated .NET 8 microservice that ensures 21 CFR Part 11 data integrity. It features Role-Based E-Signatures (Lead Scientist, Lab Tech, QA) and unique Batch ID tracking (B2026-XXX) to ensure every production run is isolated and attributed.

• Predictive HMI: A reactive Node 22/TypeScript dashboard that translates raw telemetry into predictive Batch Health Scores. It utilizes moving-window linear regression to project temperature trends 60 seconds into the future, enabling proactive intervention. 

By architecting this polyglot solution, I have demonstrated a production-ready approach to transforming raw process data into a proactive, observable, and compliant digital twin. All code is version-controlled and fully documented.

The Stack (Full-Stack Triad Architecture)

Backends (Polyglot Layer):

• Data Engine: Python 3.12, FastAPI, Pandas (High-frequency telemetry & AI Pilot logic)

• Compliance/Audit: .NET 8, C#, ASP.NET Core (Immutable GxP logging)

Frontend (Industrial HMI):

• Stack: React 18 (TS), Node 22, Recharts, Lucide-React (Real-time viz & iconography)

• Styling: CSS-in-JS, Custom Keyframes (Deterministic GxP pulsing alarm animations)

Data & Persistence:

• Storage: SQLite (Local/Edge), EF Core (Strict GxP schema enforcement)

• Optimization: Encapsulated CSV datasets for high-speed containerized data locality

Infrastructure & DevOps:

• Orchestration: Docker & Docker Compose (Multi-container parity & service isolation)

• CI/CD: GitHub Actions (Automated build/deploy pipelines)

• Cloud: Vercel (Frontend), Render (Distributed Backends)