Data Engineer (Data Platform)

Role Overview

Join Coinhako's Data Platform team as a Data Engineer where your work ensures the accuracy and reliability of every company dashboard, fraud detection signal, financial report, and AI-driven analysis. This collaborative, hands-on role involves managing and enhancing our metadata repository, ingestion and ELT pipelines, data warehouse, and internal tools critical to daily operations.

Key Responsibilities

• Develop, operate, and maintain ingestion and ELT pipelines using tools like Airflow or MWAA, integrating transactional, product event, and external data feeds.
• Transform new, untested data sources into trusted datasets for analyst consumption.
• Monitor and sustain the health of existing pipelines, including those originally developed by others.
• Enhance data quality assurance by implementing checks that prevent flawed data from contaminating reports and clearly indicate missing information.
• Perform data reconciliation against independent sources and investigate discrepancies to explain data anomalies.
• Maintain and update the metadata repository that supports pipelines, applications, and analytics.
• Provide comprehensive documentation of datasets to facilitate effortless use by analysts and AI systems without needing additional inquiries.
• Contribute to backend and data layers of internal tools, develop APIs, and maintain metadata fueling these applications.
• Assist in integrating AI technologies (such as LLM, RAG, and agentic analysis) into the data platform and its associated solutions.
• Respond to analyst and stakeholder requests, automating repetitive tasks to increase self-service capabilities.

Candidate Profile

• Possess 2 to 4 years of experience in data engineering, backend, or platform engineering roles.
• Proficient in SQL and Python programming.
• Experienced with building and managing data pipelines using Airflow or comparable workflow orchestrators.
• Familiar with cloud environments, particularly AWS.
• Demonstrate a deep understanding of system architectures, including design decisions, operational behavior, and cost implications.
• Have taken end-to-end ownership of production systems—from deployment to maintenance and troubleshooting.
• Committed to validating your own deliverables before considering tasks complete.
• Adept at working with existing code and live systems developed by others.
• Capable of authoring backend code and deploying services beyond just pipeline management.
• Communicate clearly and escalate uncertainties promptly for timely resolution.

Preferred Qualifications

• Experience within financial services, fintech, or cryptocurrency domains, especially with sensitive transactional data.
• Track record of deploying internal tools or services such as APIs, jobs, or small applications.
• Knowledge of data quality frameworks and tooling including Great Expectations, Soda, or dbt tests.
• Experience handling data where loss of events is irreversible, such as stream retention windows or APIs without historical access.

Success Indicators

• Reliable pipeline operations with prompt detection and resolution of issues.
• Prevention of data quality issues from impacting reports, dashboards, or AI analyses.
• Efficient onboarding of new data sources, simplifying future integrations.
• Reduced repetitive queries from analysts through improved documentation and self-service.
• Ability to explain incidents and improvements to prevent recurrence.
• Active integration and support of AI tools with well-documented and defendable implementations.

Work Environment & Benefits

• Engaging, friendly startup culture.
• Office conveniently situated in Singapore's Central Business District.
• Generous annual leave entitlement beyond statutory holidays.
• Comprehensive medical benefits covering general practitioners, specialists, traditional Chinese medicine, and more.
• Health and wellness perks including fitness-related workshops and webinars.
• Dynamic office space stocked with a wide variety of pantry offerings.

Additional Information

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