Data Engineer

Nahc; Hong Kong; On-site; HKD 600,000 - 900,000; Full time

Job summary

Nahc is seeking a disciplined Backend Software Engineer to own data infrastructure and build scalable ETL/ELT pipelines for financial datasets. You will ensure data integrity and design a robust data framework for reporting and analytics.

Use AI coding assistants to write cleaner code, refactor legacy modules, and accelerate the development lifecycle while maintaining high quality and performance in a fintech environment.

Qualifications

• 2+ years in Data Engineering, fintech/banking/quant trading preferred.
• Proficiency in Python or TypeScript and advanced SQL.
• Experience with async workflow libraries and time-series data.

Responsibilities

• Pipeline Architecture: Design, build, and maintain scalable ETL/ELT pipelines for complex financial datasets.
• Real-Time Event Ingestion: Architect and maintain an always-on event collection system for high-velocity data.
• Data Integrity: Implement rigorous validation and error-handling for 100% reporting accuracy.
• AI-Augmented Development: Use AI tools to generate boilerplate, refactor legacy code, and speed up development.
• System Optimization: Monitor and tune data warehouse performance and query efficiency.

Skills

Python

TypeScript

SQL

Async workflows

Time-series

AI tooling

Tools

Airflow

Job description

Overview

Our client is a forward-thinking fintech company dedicated to delivering innovative solutions for businesses in diverse industries.

They are looking for a disciplined, forward-thinking Backend Software Engineer to take ownership of their data infrastructure. You will be responsible for the architecture, maintenance, and optimization of pipelines that handle mission-critical financial data.

They are looking for an engineer who stays at the cutting edge of the field, specifically someone who has mastered the use of AI coding assistants (e.g., Cursor, GitHub Copilot, LLM-based refactoring) to write cleaner code, debug faster, and automate where possible.

Responsibilities

• Pipeline Architecture: Design, build, and maintain scalable ETL/ELT pipelines for complex financial datasets.
• Real-Time Event Ingestion: Architect and maintain an "always-on" event collection system to capture high-velocity data.
• Data Integrity: Implement rigorous validation and error-handling to ensure 100% accuracy in reporting and analysis.
• AI-Augmented Development: Proactively use AI tools to generate boilerplate, refactor legacy code, and accelerate the development lifecycle without sacrificing code quality.
• System Optimization: Monitor and tune data warehouse performance and query efficiency.

Qualifications

• Experience: 2+ years in Data Engineering, ideally within the fintech, banking, or quantitative trading sectors.
• Tech Stack: Proficiency in Python or Typescript, and advanced SQL. Experience with async workflow libraries and tools.
• Data Literacy: A solid understanding of time-series data structures.
• AI Fluency: Demonstrated ability to use AI coding tools effectively. You should be able to discuss how you use prompting or AI-integrated IDEs to improve your workflow.