AtMetis is a Dutch firm specializing in risk management, inspections, and valuations. Engineers at AtMetis frequently visit client properties—industrial or residential—to conduct assessments and generate detailed risk reports. Previously, they managed field data and client records using manual Excel spreadsheets, which proved to be inefficient, especially when using mobile devices during site visits.
As a Full-Stack Software Engineer, I led the development of a responsive, web-based File Administration System (DAS) that fully digitized the end-to-end process—from initial client intake to handoff into the Risk Management System (RMS) for final reporting.
Goals
- Replace outdated, spreadsheet-based workflow with a centralized web system
- Enable field engineers to easily input data on mobile or tablet devices
- Automate task assignments, status transitions, and cross-departmental handoffs
- Support bulk file creation from CSV uploads for institutional clients
- Ensure seamless data transfer into the Risk Management System (RMS)
My Contributions
📁 File Administration System (DAS)
I designed and implemented the DAS application to manage the lifecycle of client files. Key capabilities included:
- Responsive dashboard UI for engineers and office staff, built with Angular, TypeScript, and Angular Material
- RESTful backend with Java, Spring Boot, JPA, and Hibernate
- Automated file assignment logic: new files are routed to available engineers based on workload
- State machine–based workflow: files move through various stages—data collection, verification, reporting—until they are passed to RMS
- Role-based access for engineers and staff across departments
🧾 Bulk File Import via CSV
AtMetis often receives large requests from clients involving dozens or hundreds of properties. To streamline this process, I:
- Built a file upload UI in Angular for importing client requests in bulk
- Developed a Python + Flask microservice using Pandas to parse and clean CSV data
- Ensured smooth integration with the core Java backend for consistent data storage in MySQL
This hybrid approach allowed faster data preprocessing and improved system flexibility without overloading the core backend.
🔁 Integration with Risk Management System (RMS)
Once a file completes its workflow in DAS, it is automatically forwarded to the RMS, which uses it to generate detailed risk analysis and improvement recommendations. I ensured:
- Clean API-based handoff from DAS to RMS
- Accurate data formatting and validation
- Seamless user experience for engineers and risk consultants
Outcome
- Replaced error-prone Excel-based workflow with a centralized, secure, and mobile-friendly application
- Enabled real-time task tracking and engineer collaboration across departments
- Delivered a CSV bulk upload tool that reduced file intake time for large institutional clients
- Improved internal data quality, accountability, and handoff speed to RMS
- Boosted engineer productivity and reporting accuracy
Key Takeaways
- Hybrid architecture (Java for core logic, Python for data processing) can offer the best of both worlds when scalability and speed are key
- Field usability (responsive design + task automation) is critical for organizations with mobile teams
- Automating workflows and handoffs between systems significantly reduces delays and improves data consistency
Tools & Technologies
- Java, Spring Boot, JPA, Hibernate
- Python, Flask, Pandas
- Angular, TypeScript, Angular Material
- MySQL for relational data
- REST APIs for RMS integration