Data Engineer (Chief Data Office), Data Science & AI Division

About GovTech Singapore

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!

The Data Science & Artificial Intelligence Division partners with public sector agencies to improve policy outcomes, service delivery and operational efficiency by harnessing data science and AI. We extract data-driven insights and build intelligent platforms to add value to the work of our partner agencies. We also help them transform through building data science expertise, formulating data strategies, and setting up the necessary data infrastructure.

How We Work

• Outcome Driven – Our projects are not academic exercises. We are driven by the “so what”, and seek to ensure that our findings and models can translate into tangible impact.
• Start Small and Move Fast - We build things fast. If it works, we quickly move on to the question of how we can scale it further. If it doesn’t work, what went wrong and what can we do better next time?
• Ownership – You’re not just here to write code. Team members help to figure out what we should be building, and how we should build.
• Continuous Learning – Working on new ideas often means not fully understanding what you are working on. Taking time to learn new architectures, frameworks, technologies, and even languages are not just encouraged, but essential.
• In this Together - We draw from the deep domain knowledge of our partners and apply best practices from our community of experts.

About the Role

As a Data Engineer in GovTech’s Data Science & Artificial Intelligence Division, you will be involved in architecting, managing and running advanced analytics and data platforms. For this role, you will be working in the CDO Team within GovTech, where you will help drive GovTech’s Data Transformation efforts. You will assist to establish and implement effective operational workflows, data pipelines, procedures and best practices in accordance with government infrastructure and security policies to ensure that the platforms are monitored, secure, available and reliable.

We are looking for an independent and motivated data engineer who has experience in both small and large-scale analytics platform projects, and in building and maintaining the infrastructure.

Responsibilities

• Design, Architect, Deploy, and maintain solutions on AWS and Databricks to provide secure and governed access to data for data scientists, data analysts and business users.
• Manage the full life-cycle of a data lakehouse project from requirement gathering to data modelling, design of the data architecture and deployment.
• Collaborate with data stewards, data analysts and data scientists to build data pipelines to ingest data from enterprise systems for both batch and real-time streaming data.
• Establish and manage the complete machine learning lifecycle using MLFlow.

Requirements

• Degree in Computer Science or Information Technology or related disciplines.
• More than 4 years of experience in a technical role.
• Hands-on experience in implementing Data Lake/Data Warehouse with technologies like – Databricks, Azure Synapse Analytics, SQL Database, AWS Lake formation.
• Understanding of OLTP, Data Lake and Lakehouse technologies that may include knowledge of S3, AWS Glue, DeltaLake or DataBricks.
• Proficient in SQL, PySpark and Python.
• Experience in Big Data management & processing using tools such as Spark.
• Knowledge in Machine Learning Frameworks and the use of ML Flow to manage the machine learning lifecycle.
• Comfortable with DevOps tools like AWS Cloud Formation/Terraform, Docker and Git for CI/CD development.
• Prior experience with data engineering tools and frameworks like Airflow, Kafka, Hadoop, Spark, Kubernetes.
• Familiarity in building REST services is good to have.
• Experience in the public sector is a bonus.