Job Description

We're looking for a Data Engineer (Data Platform) to help build the systems the rest of the business runs on. Working alongside our Staff Engineer, you'll develop and support our data platform end to end — the metadata repository, the pipelines that feed it, the warehouse, and the internal web apps and AI our teams use every day.

This is the role that builds the platform. (Our Data Analysts, on Finance/Risk/Fraud, shape and validate what runs on top of it.) It's a broad brief for someone early in their career — you won't master every layer on day one, but you'll get exposure across the full stack and grow into deeper ownership over time.

Every dashboard, fraud signal, financial report, and AI-driven analysis is only as good as the data behind it. When the platform is solid, the teams that depend on it move fast and trust what they see — and that's the difference you'll make here.

You'll learn directly from an experienced Staff Engineer who owns the platform's direction, with real mentorship and a clear path toward senior data platform and architecture roles.

Day to day, your work answers questions like: Is our data fresh, complete, and reconciled with the source? Is the metadata layer easy to build on? Can the apps, analysts, and AI systems trust what they're reading, at any hour?

• Contribute to and maintain the metadata repository that pipelines, apps, and analytics depend on

• Build and run ingestion and ELT pipelines (Airflow / MWAA) that bring transactions, product events, and third-party feeds in reliably and on time

• Keep the platform healthy — uptime, performance, cost, data quality, and scaling as volumes grow

• Build and maintain the internal web apps Risk, Fraud, and Reporting rely on — expect meaningful full-stack work, including frontend

• Shape features with users, prioritise, and iterate — not just build to spec

• Integrate AI capabilities (LLM / RAG, agentic analysis) into the platform and its apps

• Provide clean, well-modelled, documented datasets both analyst teams can build on

• Partner with analysts and stakeholders to expose new sources, evolve schemas, and align on metric definitions

• Improve data lineage, documentation, and reliability

• Help manage access control, security, and the handling of sensitive financial and customer data

• 2–4 years in data engineering, backend, or platform engineering
• Strong SQL and Python
• Experience building and maintaining data pipelines and orchestration (Airflow or similar)
• Working knowledge of data models and schemas — the metadata layer other systems build on
• Full-stack ability to build and maintain web apps (backend plus frontend) on the platform
• Experience with cloud services and data warehouses (AWS preferred)
• Strong communication and a genuine eagerness to learn from senior engineers

• Financial services, fintech, or crypto experience, and handling sensitive transaction data
• Modern web frameworks (React / TypeScript, Flutter, Node) and internal-tool building
• Integrating AI / LLM / RAG into products
• dbt or a similar transformation framework
• Infrastructure-as-code, CI/CD, and streaming / CDC tooling (Terraform, GitHub Actions, Kafka, Kinesis)

• The platform is reliable — high uptime, fresh and accurate data the teams above it trust
• The metadata repository and pipelines make everything built on them easier to ship
• New sources, apps, and features go live quickly and cleanly
• Data-quality issues are caught before they reach apps, reports, or AI systems
• The platform scales with the business as analytics and AI demands grow

• Friendly and fun start-up work culture
• Convenient work location located in the heart of CBD area
• Generous annual leaves on top of national holidays
• Medical coverage including GP, Specialist, TCM, and more
• Self-care benefits and exciting fitness workshops/webinars
• Vibrant office with a well-stocked pantry

Find out more about Coinhako here [ and don't forget to visit our Careers Page [

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