Data Engineer Data Platform
Coinhako is a Singapore-based, MAS-regulated cryptocurrency trading platform. It lets users buy, sell, convert, and manage digital assets, and offers institutional services including custody and high-volume trading.
Funding
About Coinhako
Coinhako operates a cryptocurrency exchange and digital-asset platform in Singapore. Its products let users create accounts, fund them via PayNow or FAST bank transfer, and buy, sell, convert, and manage more than 200 cryptocurrencies. The company emphasizes security, regulatory compliance, and an intuitive experience for users at different experience levels. It also provides institutional services, including custody and high-volume trading solutions.
Skills
About the Role
You will build and support the data platform end to end, including the metadata repository, ingestion and ELT pipelines, data warehouse, internal web applications, and AI capabilities. You will maintain platform uptime, performance, cost efficiency, data quality, and scalability. You will build full-stack internal tools for Risk, Fraud, and Reporting; shape and iterate on features with users; and integrate LLM, RAG, and agentic analysis capabilities. You will provide clean, well-modelled, documented datasets, partner with analysts and stakeholders on sources, schemas, and metrics, and improve data lineage, governance, access control, security, and sensitive-data handling.
Requirements
- 2–4 years of experience in data engineering, backend engineering, or platform engineering.
- Strong SQL and Python skills.
- Experience building and maintaining data pipelines and orchestration with Airflow or similar tools.
- Working knowledge of data models and schemas.
- Ability to build and maintain full-stack web applications, including backend and frontend.
- Experience with cloud services and data warehouses; AWS is preferred.
- Strong communication skills and eagerness to learn from senior engineers.
Responsibilities
- Contribute to and maintain the metadata repository.
- Build and run ingestion and ELT pipelines using Airflow or MWAA.
- Maintain platform uptime, performance, cost efficiency, data quality, and scalability.
- Build and maintain full-stack internal web applications for Risk, Fraud, and Reporting.
- Shape, prioritise, and iterate on features with users.
- Integrate AI capabilities, including LLM, RAG, and agentic analysis, into the platform and its applications.
- Provide clean, well-modelled, documented datasets for analyst teams.
- Partner with analysts and stakeholders to expose new sources, evolve schemas, and align metric definitions.
- Improve data lineage, documentation, and reliability.
- Help manage access control, security, and sensitive financial and customer data.
Benefits
- Generous annual leave in addition to national holidays.
- Medical coverage including general practitioner, specialist, and traditional Chinese medicine services.
- Self-care benefits and fitness workshops or webinars.
- Well-stocked office pantry.