Senior Production/ Production Engineer (Contract)

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.

DAE’s primary purpose is to partner internal MAS functions to generate business value through the enablement of effective use of data driven insights for business value creation. This is achieved through effective strategies, strong in-house development capability, standardization of processes, tool enablement, establishing a product development mindset, promoting knowledge sharing within MAS and complementary external collaborations.

As a DAE Production Engineer, you will be working in a fast-paced environment that would require the ability to manage multiple priorities and needs of stakeholders, as well as the agility to respond to changes and developments. Specifically, you are expected to:

• 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 a strategic planner and leadership advisor

  • Develop and maintain strategic roadmaps for engineering initiatives, ensuring alignment with DAE and MAS objectives

  • Prepare and present technical proposals and business cases to senior leadership for key engineering decisions and investments

  • Translate complex technical concepts into clear, actionable insights for management of stakeholders

  • Provide regular updates to management on key engineering initiatives, risk and resource requirements

• 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

• 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