Job ref no.: CT3120276-01#0033
Foris Limited

Data Engineer - Global Fintech startup

Foris Limited

  • 5-day week
  • Discretionary bonus
  • Flexible working hours
  • Medical plan

About the company:, the pioneering payments and cryptocurrency platform, formerly known as Monaco, seeks to accelerate the world’s transition to cryptocurrency. Its MCO branded consumer financial services, including the MCO Visa Card, MCO Wallet app, and MCO Token embrace a vision of Cryptocurrency in Every Wallet™ is headquartered in Hong Kong.

MCO is redefining how money is being moved, spent and invested. MCO is democratizing blockchain technology by designing beautiful, simple and useful financial services that have a lasting, positive impact on people’s lives.

For more information, please visit: and

About the role:

The data engineering team builds the platform and improves data pipeline. We are eager to acquire talents to help achieving team and company ambitions.


  • Work with teams to build and continue to evolve data models and data flows to enable data driven decision-making
  • Design and implement alerting and testing mechanism to ensure the accuracy and timeliness of these pipelines. (e.g., improve instrumentation, optimize logging, etc)
  • Create user friendly libraries that make distributed batch computation easy to write and test for all users across company
  • Identify shared data needs across company, understand their specific requirements, and build efficient and scalable data pipelines to meet the various needs to enable data-driven decisions across company
  • Create a unified user data model that gives a complete view of our users across a varied set of products
  • Keep lower the latency and bridge the gap between our source systems and our enterprise data warehouse by refactoring and optimizing our core data pipeline jobs
  • Pair with user teams to optimize and rewrite business critical batch processing jobs in Airflow
  • Create robust and easy to use unit testing infrastructure for batch processing pipelines
  • Build a framework and tools to re-architect data pipelines to run more incrementally.
  • Estimate and control capacity and utilization of computing and storage resources in our data infrastructure


  • Have a strong engineering background and are interested in data. You’ll be writing production Scala and Python code.
  • Strong data architecture, data modeling, schema design and effective project management skills.
  • Experience with docker-related technology (docker-compose, Kubenetes, or ECS)
  • Experience in optimizing the end-to-end performance of distributed systems.
  • Experience with large data sets, Hadoop, and data visualization tools
  • Familiar with designing and implement infrastructure on AWS or Google Cloud
  • Experience in managing and designing data pipelines can follow the flow of data through various pipelines to debug data issues.
  • Ability to initiate and drive projects, and communicate data warehouse plans to internal clients/stakeholders
  • Bonus:
  • Have experience with Spark
  • Have experience with Airflow or other similar scheduling tools.
  • It’s not expected that you’ll have deep expertise in every dimension above, but you should be interested in learning any of the areas that are less familiar.

What you can expect from us?

  • We offer an attractive compensation package working in a cutting-edge field of Fintech
  • Exploring and learning latest technologies through your work, including but not limited to: Big Data, Blockchain
  • Huge responsibilities from Day 1. Be the owner of your own learning curve. The possibilities are limitless and depend on you
  • You get to work in a very dynamic environment and be part of an international team
  • You will get to have involvement in developing a brand new product from scratch alongside with a talented team 

Interested parties please click Apply Now to apply job

More job information
Job ref no. CT3120276-01#0033
  • N/A
Job Function
Employment Term
  • Permanent
  • Full-time
  • 2 years - 5 years
Career Level
  • Non-management level
  • Degree