Lead Data Engineer - Singapore

Software Engineers
Full Time
Xfers Mission
Xfers believes in financial inclusion. We abstract away regulatory and compliance responsibilities, making it easy for Fintech and digital businesses to accept payments, store and disburse funds.

In Singapore, we are a Widely Accepted Stored Value Facility alongside only 4 other companies, namely Capitaland, Ezlink, Cashcard, and NETS.

In Indonesia, we are a registered payments gateway licensee. We work closely with regulators to ensure that our services are compliant.

About The Role
As a Data Engineer at Xfers, you are responsible to working with the data engineering team and setting up our data infrastructure to support our growing data needs.

At Xfers, you will be exposed to the unique data challenges in the growing SEA payments industry and learn about new, emerging trends in financial technology.

You will lead our data engineering team and work with product, design, and other teams to deliver a world-class (no less) data infrastructure for our deep financial systems

For this role, we are looking for high potential individuals on a high growth trajectory that are able to demonstrably lead a small team but has the potential to grow with us as we scale

Who are we looking out for

    • You manage complexity well, able to break down complex solutions into clear, understandable chunks
    • You are an emergent leader. You step up to leadership but also step back and support when others have a better direction
    • You are humble and egoless about your work. You seek help often, share credit and are great at receiving and delivering feedback
    • You are always learning, questioning the status-quo, gathering knowledge and looking to improve
    • You are responsible. Other team members can fully trust that you can execute on your tasks
    • You are a great communicator and work exceptionally well with others


    • 3 - 5 years of Data Analyst or Data Engineering Experience
    • BS/MS Degree in any relevant major. (ex: IT, Computer Science, Quantitative finance, etc) 
    • Deep experience with Data Engineering Toolchains ( Airflow, Spark, Hive etc )
    • Experience with the different databases and how they work together
    • Knowledge of commercial reporting tools and technologies and comfortable handling large data sets.
    • Excellent analytical and problem-solving skills with the ability to process a high amount of data to drive business strategies and decisions
    • Experience with data warehousing and data engineering