Data Engineer

Data Engineer, M-DAQ 

 

 

About M-DAQ Pte. Ltd.

 

M-DAQ builds over-the-top (OTT) applications to facilitate cross-border business for various industries. These include securities markets, e-Commerce platforms and payment solutions providers. M-DAQ achieves this through our proprietary technology, together with the remittance license awarded by the Monetary Authority of Singapore. M-DAQ was awarded “Best Tech Company To Work For 2019” by Singapore Computer Society (SCS).

 

M-DAQ is a high-growth FinTech start-up that focuses on proprietary best-in-class corporate FX solutions across Asia. We have to date processed over $10 billion in FX transactions and generated hundreds of millions of dollars in revenue for our partners and savings for their end-customers. Having recently concluded our Series D financing round, we have exciting plans to leverage our FX expertise in even more verticals.

 

 

Why Us? 

 

  • Have a positive impact to the world’s economy by creating a World without Currency BordersTM
  • Team Innovation Mindset, People-Oriented
  • Challenging environment, offering great opportunities to learn and grow
  • Creative and Innovative Workplace

 

Roles & Responsibility:

  • Design, develop and implement Big Data platforms in cloud
  • Build a centralized datalake and data warehouse for data feeds from all M-DAQ entities
  • Set up tools for data ingesting (batch and real-time), data cleaning, building data cubes in the data warehouse
  • Build tools to monitor data quality and manage data changes
  • Build end-user facing data catalogue and data lineage to facilitate data discovery

 

Requirements:

  • 5+ years of experience with excellent coding skills (Python, Java or Scala)
  • Bachelor or Master’s degree in Computer Science, Engineering, or relevant industry experience is required
  • Experience with Big Data technology architecture (Hadoop, Spark, Kafka, Flink, Hive etc), tuning, troubleshooting and scaling the systems. Deep understanding with the internal principles of these systems.
  • Hands on experience designing and implementing Data Warehouse (Snowflake, Athena or Redshift)
  • Solid understanding of ETL and ELT approaches and large scale data ingestion/integration framework.
  • Experience in designing data quality morning and fault-tolerant pipelines
  • Hands on experience in developing/designing/integrating using Kubernetes
  • Exposure in building real-time processing pipelines using Flink or Spark-streaming
  • Exposure to data and machine learning services from Amazon Web Services (AWS) and/or Google Cloud (GCP) is a plus

 

 

What We Offer: 

 

M-DAQ offers competitive remuneration including employee stock options and employee benefits.