Staff Data Engineer

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About DKatalis

DKatalis is a financial technology company with multiple offices in the APAC region. In our quest to build a better financial world, one of our key goals is to create an ecosystem-linked financial services business. DKatalis is built and backed by experienced and successful entrepreneurs, bankers, and investors in Singapore and Indonesia who have more than 30 years of financial domain experience and are from top-tier schools like Stanford, Cambridge London Business School, JNU with more than 30 years of building financial services/banking experience from Bank BTPN, Danamon, Citibank, McKinsey & Co, Northstar, Farallon Capital, and HSBC.

About the role

Lead the design and evolution of our organisation’s data infrastructure, ensuring it operates as a robust, resilient, and highly automated ecosystem. You will be responsible for the technical roadmap of the data platform, mentoring engineers in your squad, and driving cross-functional alignment to deliver high-impact digital products.

What will you do

• Technical Leadership: Leading the design and scaling of data infrastructure; overseeing the architecture of complex ETL pipelines (batch/streaming) to ensure system resilience.

• Data Excellence: Driving standards for data model design, quality frameworks, and high-quality metadata across multiple squads.

• Governance & Security: Implementation of automated data governance tooling and ensuring all squads adhere to privacy policies and procedures.

• Strategic Collaboration: Partnering with Product and Engineering owners to design and refine the data product from concept to implementation.

• Mentorship & Coaching: Mentoring budding engineers in good engineering practices and fostering a culture of constructive public and private feedback.

• Operational Excellence: Continuously improving code quality, product execution, and automation while balancing perfection with timely value delivery.

What you need to have

• You have at least 10+ years of professional experience in software/data engineering, building highly scalable applications.