Data Generator & File Processing
A JavaScript/Electron desktop application I built to create and edit test and internal referral data, package files, and support uploads for United States Department of Veterans Affairs lower-environment workflows.
- My role
- Application developer and maintainer
- Context
- Internal data tooling
- Period
- Ongoing
- Employer
- Booz Allen Hamilton
- End customer
- United States Department of Veterans Affairs
Private source. GitHub access requires repository permission.
01 / Challenge
The delivery problem.
Internal teams needed a repeatable way to generate large volumes of referral data and customize the data to suit their specific workflows and use cases.
Who needed it: Internal teams that need to generate and modify referral data for different testing and operational workflows.
02 / Approach
What I personally built.
- 01
Independently built and continue to maintain Data Generator & File Processing for generating and editing referral data.
- 02
Provide a desktop workflow for editing existing JSON, generating new files, and preparing combined data and gzip packages.
- 03
Support uploads to configured targets, with explicit status and retry handling for failed destinations.
- 04
Demonstrate updates, troubleshoot daily use, and document workflows so teammates can use and extend the tool.
03 / Outcome
What changed.
User-reported: QA uses Data Generator & File Processing daily to prepare and upload hundreds of referrals in minutes.
- Application development and maintenance
- Referral data generation and editing
- JSON and gzip file preparation
- Upload status and explicit retry handling
04 / Systems & decisions
APIs, data, and infrastructure.
Electron provides the desktop window, dialogs, and IPC between the renderer and backend logic.
The file workflow reads and writes referral JSON and produces combined data and gzip archives.
Uploads use configured targets through SFTP or WinSCP. This is a desktop file-processing workflow; the United States Department of Veterans Affairs claims application is a separate project.
The repository documents a Windows installer and a GitHub Actions release workflow. No internal targets or upload settings are published here.
Constraints and tradeoffs
- A desktop application supports local file selection, processing, and packaging; it also requires Windows installation and update handling.
- A sequential upload queue attempts each destination once per run, continues after a failure, and offers explicit retries for failed destinations.
- Completion reporting distinguishes completed destinations from transfer-byte progress; SFTP completion checks the remote file size.
05 / Evidence
What you can inspect.
Repository-documented implementation
The private repository README documents Electron UI/backend separation, JSON editing and generation, gzip packaging, and upload handling. Source access requires repository permission; no public demo is available.
Reported team use
Daily QA adoption and hundreds of referrals in minutes are user-reported outcomes, not independently measured public benchmarks.
How this supports my FDE direction
Data Generator & File Processing shows how I turn a recurring team need into a usable tool, connect an interface to data processing and external systems, and support adoption over time.
06 / Toolkit
Tools in context.
This account is derived from documented career responsibilities. Client-sensitive details are intentionally generalized, and no undisclosed metrics are presented.