Data Engineer, Data and Artificial Intelligence Platforms (DAIP) .

Description and Requirements

The Government Technology Agency (GovTech) is the lead agency driving Singapore’s Smart Nation initiatives and public sector digital transformation. As the Centre of Excellence for Infocomm Technology and Smart Systems (ICT & SS), GovTech develops the Singapore Government’s capabilities in Data Science & Artificial Intelligence, Application Development, Smart City Technology, Digital Infrastructure, and Cybersecurity.
At GovTech, we offer you a purposeful career to make lives better. We empower our people to master their craft through continuous and robust learning and development opportunities all year round. Our GovTechies embody our Agile, Bold and Collaborative values to deliver impactful solutions.
GovTech aims to transform the delivery of Government digital services by taking an "outside-in" view, putting citizens and businesses at the heart of everything we do.
Play a part in Singapore’s vision to build a Smart Nation and embark on your meaningful journey to build tech for public good. Join us to advance our mission and shape your future with us today!
Learn more about GovTech at tech.gov.sg.

Who we are
The mission of GovTech's Data and Artificial Intelligence Platforms team is to deliver high-quality reusable Data and AI assets and services for policy making, service delivery and operations across WOG.

What the products are
We are seeking a Data Engineer to join our Data and Artificial Intelligence Platforms (DAIP) team. The existing Government Data Architecture (GDA), launched in 2019, laid the groundwork for WOG data sharing via TCs, SSOTs and central platforms. As the data technology landscape is rapidly evolving and data/system requirements are becoming increasingly complex and interconnected, to better support agencies, the next phase of GDA (i.e. GDA 2.0) aims to consolidate, streamline, and elevate the products and initiatives within the WOG data landscape – this includes the development of the following products.

• DataHive as the next-gen WOG Data Discovery & Request Platform to cater to a wider range of WOG requirements and use cases. DataHive has been further enhanced to support both data requestors and providers as follows. 1) Data requestors/consumers will experience a streamlined data search and request process, with options to access data via curated APIs and through an analytics workbench. 2) Data providers can expect more flexibility and control in the management of datasets on the platform itself.
• Data products that compute and serve derived data for ops and service delivery for multiple agencies. By adopting the “Build Once, Use Many Times” approach for such data products, the intent is to achieve the benefit of cost-savings, better data quality and improving time-to-market for new services.
• Fraud Detection Platform (FDP). FDP is a central platform for Grant Fraud Insights. It draws data from TC Business & Individual, combines it as a graph and generates insights on businesses and individuals for government grant, procurement and finance due diligence checks and audits.

What you will be working on

As a data engineer, you will:

• Architect and build ingestion pipelines to collect, clean, merge, and harmonize data from different source systems.
• Monitor databases and ETL systems, e.g., database capacity planning and maintenance, monitoring, and performance tuning; diagnose issues and deploy measures to prevent recurrence; ensure maximum database uptime.
• Construct, test, and update useful and reusable data models based on data needs of end users.
• Design and build secure mechanisms for end users and systems to access data in data warehouse.
• Research, propose and develop new technologies and processes to improve agency data infrastructure.
• Collaborate with data stewards to establish and enforce data governance policies, best practices and procedures.
• Maintain data catalogue to document data assets, metadata and lineage.
• Implement data quality checks and validation processes to ensure data accuracy and consistency.
• Implement and enforce data security best practices, including access control, encryption, and data masking, to safeguard sensitive data.
• Learn and share knowledge in a multi-disciplinary team.

Additionally, more senior engineers will be expected to:

• Establish best practices.
• Share your expertise and mentor other engineers.
• Help with recruiting.