Data Engineer, Government Infrastructure Group


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Job Summary

$6,000 - $10,000 SGD / Monthly EST

Job Type


Years of Experience
At least 2 years

Tech Stacks

Job Description

Join us as we support Singapore’s vision of building a Smart Nation - a nation of possibilities empowered through info-communications technology and related engineering.

Government Infrastructure Group (GIG)

The Government Infrastructure Group (GIG) is responsible for digital infrastructure that supports the Whole-of-Government (WOG). We are the infrastructure architects and engineers who architect, design and deliver an agile, secure and sustainable infrastructure which enables a digital government for Singapore.

How We Work

Aside from formulating the infrastructure strategy and roadmap at WOG level, we also develop prototypes using new technologies and establish standards to guide the design and implementation of information systems that support the enterprise infrastructure.

We examine factors such as people, culture, policies and processes to provide a secure, predictive and always-on platform, enabling public officers to work anywhere and anytime.

By using innovative Cloud and SaaS technologies, we architect, design, build and deliver Cloud and Datacentre hosting environments and common services which support government agencies in accelerating and developing modern applications and services.

Redefining ICT infrastructure through modernisation and automation is also our key focus. Using the latest technology and best practices, we deliver secure and utility-based services to WOG, so that government agencies can function efficiently and seamlessly.

We are also passionate about building and uplifting ICT engineering know-how for the WOG in critical infrastructure domains, which we advance through experimentation, prototype development, consultancy and training.

Job Overview

As a Data Engineer, you will be part of the data analytics team to modernise and streamline the Whole-of-Government (WOG) Infrastructure using data to provide insights needed for evidence-based decision-making and improving the delivery of WOG services. You will be architecting, designing, building and operating the next-generation data infrastructure to galvanise digitalisation in the public sector.

You will collaborate with peers such as product manager, data analyst Hadoop system engineers, software engineer to conceptualise the data pipeline to provide data driven insights for users from Whole-of-Government (WOG).

What To Expect

  • Involve in the design and building of resilient and efficient data pipelines for both batch and real-time streaming data
  • Involve in the architecture, design, implementation and maintenance of data infrastructure using industry standard infrastructure-as-a-code tools
  • Build and implement framework to resolve data problems at scale
  • Mange the continuous testing and development of data pipeline, new data sources and analytic dashboards.
  • Execute projects with Agile methodologies
  • Collaborate with product managers, software engineers and data analysts to build scalable and data-driven platforms and tools

How To Succeed

  • Bachelor’s Degree in Computer Science or have equivalent professional experience
  • Have at least 2 years’ experience in python and SQL
  • Passion for problem-solving, improving and/or implementing processes
  • Experience implementing batch and streaming data pipelines.
  • Experience in handling Warehouse operation data
  • Knowledge of both SQL and NoSQL databases, including performance tuning and troubleshooting.
  • Familiar with DevOps tools such as Git, Docker, Terraform
  • High analytical ability - critical and logical thinking and optimization.
  • Ability to deliver on timelines and move quickly with multi-functional teams to execute on decisions while maintaining attention to details
  • Team player with strong analytical thinking and problem-solving skills.
  • Experience in the public sector is an advantage
  • Knowledge in SCRUM or DevOps.
  • Knowledge of ITIL processes and procedures.

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