Data Engineer (Capital Markets / FinTech) 75k

This role focuses on building and maintaining enterprise-grade data platforms, ETL pipelines, and cloud-based data solutions. The ideal candidate brings strong Java/Python expertise, extensive data engineering experience, and knowledge of financial market operations.

Our client is a professional organization operating in a data-intensive and technology-driven environment. The team focuses on enterprise data management, platform development, integration, governance, and analytical enablement across complex business functions.

• Design and develop scalable ETL workflows for both real-time and batch data processing using enterprise integration platforms, while building high-performance production applications in Java and Python.
• Standardize, validate, and cleanse data originating from multiple systems, and create automated processes to enforce and monitor data quality.
• Manage data transfers and schema evolution across a broad database landscape, including relational, object-oriented, and NoSQL technologies.
• Develop and maintain conceptual, logical, and physical data models for transactional and analytical platforms, supported by comprehensive data documentation.
• Deliver robust cloud-based data solutions and implement the ingestion, transformation, and structuring of distributed ledger data within secure environments.
• Lead collaboration forums focused on data initiatives, gather requirements from business stakeholders, translate operational needs into data structures, and provide advanced technical support to analytics functions.
• Establish and maintain frameworks covering data security, access governance, and ongoing data quality monitoring.

• Bachelor's degree or above in Information Technology, Computer Engineering, or a related discipline.
• Minimum 7 years of software development and data engineering experience within capital markets, financial technology, or closely related financial environments, with strong understanding of the end-to-end trade lifecycle.
• Strong hands-on expertise in both Java and Python, together with proven experience in data modelling methodologies and technical documentation.
• Practical experience working with enterprise databases such as Oracle, PostgreSQL, GaussDB, OceanBase, NoSQL platforms, or object-oriented database systems.
• Experience working within both public cloud and private cloud environments.
• Strong communication skills with the ability to engage business users for requirements analysis and reporting activities.
• Fluency in English and either Cantonese or Mandarin.

• Temporary role with opportunities to contribute to impactful data projects.