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[What the role is]
MAS's Data Analytics & Engineering (DAE) Division is a specialised team within the Data Technology and Architecture (DTA) Department within the Technology Group (TG) in MAS.[What you will be working on]
Be a technically skilled leader grounded on best practices
Be accountable for and drive production engineering related initiatives with a team of skilled production engineers
Be directly responsible for the delivery of the complex production engineering projects within DAE
Establish production engineering best practices, day 2 operating models, methodologies, and standards across team and MAS
Stay up to date on emerging methods and technologies that complement data science trends
Be an effective communicator and collaborative partner
Collaborate effectively with DAE's Data Science (DS) and Product Management (PM) teams to translate and host data science products on enterprise data science platforms (EDSPs) owned and managed by the PE team
Work with other TG divisions such as Platform Architecture and Engineering (PAE), Cyber Security (CySD) and Data Collaboration Platforms (DCP), and identify requirements to enable scalable and secure EDSPs that are well integrated within MAS's data and enterprise architecture
Promote the growth of the Data Analytics Community of Practitioners (DACoP) through organisation of workshops, training sessions, and forums to foster greater awareness of engineering best practices within MAS
Be a supportive team player
Support any TG, DTA, DAE initiatives as required.
Strengthen DAE's positive and open working norms
[What we are looking for]
Bachelor's degree, preferably in Computer Science, Information Systems Management, Engineering, or another related field.
Excellent platform and data engineering skills, with a 3-10 years of prior experience delivering enterprise data science or big data platforms within public service and/or financial services industry
Good understanding of Traditional and Generative AI / data application development (Python) and / or networking protocols and services
Familiarity with various database technologies such as MSSQL and PostgreSQL. Working experience with both structured and unstructured datasets a must
Experience setting up AWS or GCP services a plus
Working experience with Version Control (e.g.: Bitbucket, Gitlab) and Continuous Integration / Continuous Deployment platforms (e.g.: Gitlab, Jenkins) with added advantage for Container Management (e.g.: Kubernetes, Docker, AWS ECS), Terraform and Ansible, either On Premise or Cloud
Good appreciation of common cybersecurity risks and controls
Experience in analysing findings from Vulnerability Management tools (e.g.: Amazon Inspector, SonarQube, NexusIQ, Twistlock and Tenable) and rectifying code, supply-chain and / or security findings.
Knowledge on configuring popular operating systems such as Linux and Windows and / or Middleware such as Apache, Nginx, gunicorn against CIS standards
Comfortable working on multifaceted problems in an agile environment. Demonstrate passion and ability in overcoming business and technical constraints and deliver platforms necessary to productise data science products in MAS
Strong presentation and communication skills. Ability to explain technical concepts to a non-technical / business / senior management audience is a must
As part of the shortlisting process for this role, you may be required to complete a medical declaration and/or undergo further assessment.
This contract is a 2-year contract. All applicants will be notified on whether they are shortlisted or not within 4 weeks of the closing date of this job posting.
Date Posted: 26/09/2025
Job ID: 127164235