[DS] Data Product Engineer｜資料應用工程師

■ 團隊介紹

• 在 Net Protections (TW)，我們經營 BNPL (後支付) 金融服務，打造資料洞察驅動的產品與營運體系。
• 我們重視扁平且彈性的文化，團隊精實，並與需求方及工程緊密協作。
• 在 Data Science Team 資料技術上以 AWS 生態系為核心，並導入 Claude Code 等 AI 工具，大幅縮短從原型到產品的開發週期。
• 我們尋找能開發多元產品（從 0 到 1 及現有系統優化）、且能用資料判斷該做什麼的夥伴。若你想透過技術創造商業價值，這是你的舞台。

■ 職位描述

• 開發與優化產品：善用 AI 工具 (如 Claude Code) 負責從 0 到 1 新產品開發或現有系統優化，將商業假設轉為真實產品。
• 建立 Pipeline 與後端服務：設計與實作各類應用的端到端 Pipeline 與架構，確保穩定、可擴展且貼合商業目標。
• 資料洞察驅動開發決策：主動以資料評估功能價值與優先級，影響你自己 Sprint 的開發順序與方向。
• 跨部門協作：與 Data Scientist 緊密合作，將模糊商業需求轉化為清晰的技術方案與交付。

■ 應徵條件

• 經驗要求：1 年以上產品開發經驗，有完整參與端到端 (End-to-End) 專案上線實績。
• 後端與架構能力：熟練 Python 及 API 開發 (FastAPI、Flask)；熟悉 Git 版控與 CI/CD Pipeline 基本概念。
• 資料工程基礎：熟悉 SQL 與 dbt，具備資料 Pipeline (ETL、資料模型、批次/即時處理) 實作經驗。
• 商業意識：理解產品背後的商業邏輯，主動思考「為什麼要做」而不只是「怎麼做」。
• 溝通協調能力：能與非技術夥伴清楚討論技術 Trade-off，具備中英文工作溝通能力。

■ 加分項目

• 具備 AI 開發工具 (Claude Code/Cursor) 或 LLM / Agent 應用實作經驗。
• 熟悉 AWS Serverless 生態系 (Lambda, DynamoDB 等) 及 CI/CD 自動化部署 (CodePipeline, ECR)。
• 具備 Fintech / 電商經驗，或曾參與 ML/MLOps、推薦系統、實驗分析平台的開發。
• (建議提供) 展現商業問題解決能力與技術方案規劃的作品集或 GitHub。

■ About the Team

• At Net Protections (TW), we operate BNPL financial services and build a data-driven product engine.
• We value a flat, lean culture and collaborate directly with stakeholders and engineering.
• In Data Science Team, powered by the AWS ecosystem and AI tools like Claude Code, we drastically shorten the path from prototype to production.
• We're looking for someone to build diverse products (0-to-1 and system optimizations) and drive decisions with data. If you want to create business value through engineering, this is your stage.

■ Job Description

• Develop & Optimize Products: Use AI tools like Claude Code to build 0-to-1 products or optimize existing systems, turning business hypotheses into usable products.
• Build Pipelines & Backend Services: Design end-to-end architectures and pipelines for diverse applications, ensuring stability, scalability, and business alignment.
• Data-Driven Decisions: Proactively use data to evaluate feature value, prioritize tasks, and shape your own sprint direction.
• Cross-Functional Collaboration: Work closely with Data Scientists to translate fuzzy business needs into clear technical deliverables.

■ Requirements

• Experience: 1+ years of product development experience with an end-to-end project track record.
• Solid Backend & Architecture: Proficient in Python/APIs (FastAPI, Flask); familiar with Git and basic CI/CD concepts.
• Data Engineering Foundation: Proficient in SQL and dbt, with hands-on data pipeline design (ETL, modeling, batch/streaming).
• Business Awareness: Understands business logic and proactively asks "why we build" instead of just "how".
• Communication: Able to discuss technical trade-offs with non-technical peers. Professional Chinese and English proficiency.

■ Nice-to-Haves

• Experience with AI development tools (Claude Code/Cursor) or LLM/Agent applications.
• Familiarity with AWS Serverless (Lambda, DynamoDB, etc.) and CI/CD automated deployments (CodePipeline, ECR).
• Background in Fintech/e-commerce, or experience with ML/MLOps, recommendation systems, or A/B testing platforms.
• (Highly Recommended) Portfolio/GitHub showcasing business problem-solving and technical delivery.