AVP/VP, Data Engineer

  • Attractive
  • Singapore
  • Permanent, Full time
  • GIC Private Limited
  • 12 Dec 17 2017-12-12

The Data & Analytics Department (DAD) is responsible for the positioning and development of GIC as an information centric business, by effectively harnessing the total GIC knowledge and investment data available from internal and external sources. DAD would be responsible for leveraging on data science and research at the enterprise level, facilitating enterprise-wide governance on information and developing an integrated knowledge architecture to process, analyse and mine data for better investment decisions. We are looking for a suitable candidate to join our Data & Analytics team as a Data Engineer.


  • As a full-stack software engineer, to build, enhance and maintain a distributed computing platform and implement machine learning algorithms on large scale data in production.
  • Work closely with data scientists to understand various data science models and research, and construct efficient and scalable algorithms to implement these in production.
  • Set up strong foundational procedures, guidelines and standards for data analytics and processing.
  • Build reusable software libraries and tools for data load testing, processing and analysis.
  • Build automated pipelines for developing, testing and deploying data analytics applications.
  • Integrate new software tools for data analysis into the existing toolset.


  • Bachelor degree or equivalent in Computer Science, Data Science or Engineering degrees.
  • Production working experience with Hadoop and Spark.
  • Technical expertise in one or more of the following languages:  Java, Scala, C++.
  • Good working knowledge in one or more of the following: R, Python, NoSQL (e.g. Mongo, Cassandra), SQL.
  • Deep understanding of algorithms and algorithmic complexity.
  • Experience building and maintaining production machine learning models at large data scale.
  • Having a systems orientation approach to software design and operations.
  • Strongly disciplined approach to software development and production operationalization:  version control, code review, automated unit and integration testing, regression testing, automated deployment, runtime monitoring.
  • Experience in implementing delivery pipelines on Jenkins or other similar CI/CD platforms.
  • Good team worker, eager to learn, strong analytical skills, with good communications and interpersonal skills.