[What the role is]
The Logistics Data & Analytics team sits within Enterprise Singapore's Supply Chain and Logistics Resilience division. The team develops, manages and enhances logistics data platforms and infrastructure. Additionally, they maintain Enterprise Singapore's logistics stock data platform, and is expanding its capabilities to build a comprehensive situational awareness picture for crisis operations, as part of EnterpriseSG’s role as Whole-of-Government (WOG) Logistics Sector Resilience Lead and Lead for Coordinated WOG Crisis Distribution. The team also drives AI adoption within the logistics industry, supporting both broadbased and growth accounts in leveraging data and AI for operational improvements.
As a Data Manager/Engineer, you will be responsible for maintaining and enhancing the data platform, developing data infrastructure for logistics flow data, and integrating AI capabilities to support both crisis operations and industry development objectives. Further, you will lead the translation of crisis-distribution operating needs into data products, platform enhancements, dashboards, interfaces, and runbooks. You will work with internal users, WOG agencies, GovTech/technology teams, vendors, and logistics industry partners to ensure that logistics stock, flow, and capacity data are timely, trusted, secure, and decision-ready during peacetime planning and crisis activation.
[What you will be working on]
- Maintain and enhance the logistics stock data platform, ensuring data security, performance, and an improved UI/UX experience for end users
- Plan and execute the migration of the data platform to the Government Commercial Cloud (GCC+) in line with government data infrastructure requirements
- Build and maintain APIs and automated ETL/ELT pipelines
- Implement data quality monitoring, observability and automated validation
- Develop data infrastructure and pipelines for logistics flow data to support comprehensive situational awareness for crisis operations
- Integrate the data platform with public and private sector interfaces to enable seamless data exchange across the logistics ecosystem
- Introduce and implement AI capabilities within the data platform to facilitate sensemaking, analytics, and decision support
- Drive catalytic AI use cases for broadband and AI-for-growth accounts within the logistics industry
- Collaborate with internal stakeholders and external partners to identify data requirements and translate them into technical solutions
- Ensure data governance, security, and compliance standards are upheld across all platforms and pipelines
- Monitor platform performance and proactively identify areas for improvement and optimisation
- Support crisis operations by ensuring real-time data availability and reliability across logistics data systems
- Document technical architecture, data flows, and system configurations to maintain clear and up-to-date records
- Feature Engineering based on existing geospatial and network datasets to support logistics situational awareness
- Support crisis exercises by ensuring systems, dashboards and pipelines remain activation-ready
[What we are looking for]
- Degree in Computer Science, Information Systems, Data Engineering, or related discipline
- Minimum 3-5years of relevant experience in data engineering, platform management, or analytics infrastructure development
- Strong SQL and Python programming skills
- Experience with Spark, Databricks or equivalent distributed processing frameworks (advantageous)
- Experience developing REST APIs and integrating enterprise systems
- Experience working with geospatial data (advantageous).
- Proficiency in data pipeline development, ETL processes, and cloud-based data infrastructure
- Experience with cloud migration, preferably with familiarity with Government Commercial Cloud (GCC) or similar environments
- Stong knowledge of data security principles and best practices
- Experience integrating data platforms with external public and private sector interfaces and APIs
- Familiarity with AI and machine learning tools and their application in data analytics and sensemaking
- Experience in UI/UX considerations for data platforms and dashboards
- Strong understanding of data governance frameworks and compliance requirements
- Experience working in logistics, supply chain, or operations data environments (advantageous)
- Familiarity with crisis management or operational situational awareness systems (advantageous)
- Excellent communication skills with ability to translate technical concepts for non-technical stakeholders
- Strong problem-solving skills with ability to work effectively under ambiguity and evolving requirements
How We Work Together
We value individuals who work well with others, communicate clearly, take ownership of their work, and are open to learning and improvement. You should be comfortable navigating change and contributing positively to a collaborative team environment.
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