AVP/VP, Data Engineer, Research Data Engineering

Data Strategy Group
Data Strategy Group (DSG) harnesses and leverages on GIC's most valuable asset - Data, to drive insights, results and solve real business challenges. We ingest, analyze, and combine data with context across all industries and asset classes to enable investment decisions and enhance investment process. Together, we strive to build a high-performance enterprise data infrastructure, create results-driven approach with data products and strive to be a data-driven organization.

You will be part of the Research Data Engineering team, playing a key role in expanding and optimizing our data and data pipeline architecture, as well as looking after the operation and requests from multi-functional teams.
In your new role, you will have the opportunity to engage in building GIC's data foundation and infrastructure with a team of forward-looking data professionals. Join us and make a difference in our data journey to shape our world of investments.

Responsibilities

• Work closely with data product team and business end-users to implement and support data platforms using best-of-breed technology and methodology
• Design and build robust and scalable data ingestion and data management solutions for batch-loading and streaming data sources
• Work closely with data governance team to build the data quality check framework and ensure the data issues are monitored, tracked, and fixed without breaching SLA
• Work with members in the team to establish best practice and internal processes to enhance the data pipeline operations

Requirements

• Bachelor's degree in Computer Science, Computer Engineering or equivalent
• At least 5 years' experience of working as a data engineer or backend developer in a big data field
• Solid working knowledge of implementing the optimal data structures and algorithms to create efficient and scalable applications in Java or Python
• Familiar with application integration with RDBMS. Working knowledge of Oracle and MS-SQL will be a plus
• Hands-on experience of using Linux (or Unix-like OS) as the development environment and familiar with shell scripts and command line tools in Linux/Unix environment
• Exposure and knowledge in the following technologies is advantageous:
  • Java, Python, Shell Script, Informatica, Node.js
  • Snowflake, Oracle, MS-SQL
  • IBM-MQ, Kafka, Amazon Kinesis, Apache Flink
  • AWS (EC2, S3, EMR, SNS, CloudWatch, Athena)
  • Docker, Kubernetes
  • Data Virtualization - Denodo
• Experienced with the Systems Development Life Cycle implementation methodology (SDLC) and/or agile methodologies like Scrum and Kanban
• Understand and apply the good industry practice of code versioning, testing, CICD workflow and code documentation
• Good team player, with strong analytical skills and enjoy complex problem solving with innovative ideas
• Good communication/people skills required to interact with data analysts, business end-users and vendors to design and develop solutions
• Good at working with details and is meticulous for operations