Andrew Nguyen

Software Engineer · since 2024Based in Vietnam · open to relocationLooking to work in JapanJapanese — studying toward JLPT N4
紹介About

Full-stack engineer in construction-tech — web apps, data pipelines and AI document processing, from React on the front to .NET and AWS behind it.

ReactTypeScript.NETPostgreSQLAWSAirflowPythonAG Grid
作品Works
作品Mar 2026 – PresentCase study

Data Warehouse

AI delivery-order data pipeline

AIPDF → data
Multi-vendoringest
Airflow+ Lambda
Apache AirflowAWS LambdaPython.NETPostgreSQLReact

A data warehouse for rebar delivery orders (DOs). It pulls delivery documents from steel suppliers and scanned / WhatsApp uploads, uses AI to read each PDF into structured data, deduplicates and reconciles deliveries against purchase orders, and serves everything through a web app — orchestrated with Apache Airflow over AWS Lambda.

Overview

Construction sites receive rebar against delivery orders from many suppliers, almost always as PDFs. This warehouse centralises every DO — from supplier portals, scanned packages and a WhatsApp intake flow — into one queryable source of truth, with AI extraction replacing manual data entry.

Role

Full-stack + data engineering — .NET back end, React front end, and the Airflow pipelines (scanned-DO and per-supplier sync) wired to the AWS Lambda functions.

Highlights

  • Per-supplier connectors — each vendor has its own fetch → download → split flow (with EventBridge relays and fan-out PDF downloaders), triggered on a schedule or on demand.
  • AI document extraction — Lambdas split package PDFs into per-DO pages and read them into structured rebar data with vision LLMs, using company-aware prompts and automatic DO-type classification.
  • Dedup & reconciliation — new deliveries are deduped against the warehouse, then DO line items are matched back to purchase-order items (including vision-based matching) and vendor names normalised.
  • Airflow orchestration — TaskFlow DAGs with dynamic fan-out, bounded concurrency to protect database connections, retries and WhatsApp failure alerts.
  • Multi-source ingest — one pipeline serves supplier APIs, scanned uploads and a WhatsApp intake flow.
  • Web app — React/TypeScript + AG Grid front end on a clean-architecture .NET / PostgreSQL back end for browsing and managing delivery orders.

Outcome

Replaced manual rebar-DO entry with an automated, multi-source pipeline — supplier syncs and scanned / WhatsApp uploads land as clean, reconciled records in a single warehouse.

Technologies

Data & orchestration: Apache Airflow (Python), AWS Lambda, EventBridge, SQS / SNS · AI: PDF → structured extraction with vision LLMs · Backend: .NET, EF Core, PostgreSQL · Frontend: React, TypeScript, AG Grid

経歴Experience
May 2024 –Full-time
Software Engineer
Woh Hup (Private) Limited · Singapore
Full-stack construction-tech platforms — React · .NET · PostgreSQL.
Aug 2025 –Freelance
Software Tester
Applause App Quality, Inc · USA
Remote freelance QA — testing across web & mobile.
2022 – 2024
Freelance Web Developer
Remote
Built websites and web apps for clients.
2021 – 2024
Bachelor's · Construction Informatics
Hanoi University of Civil Engineering
Faculty of Information Technology
記録Writing
Open to opportunities · Japan
Hanoi --:--Tokyo --:--
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