Key Responsibilities
- Support the stakeholder engagement, development, implementation and maintenance of systems for data collection, storage, access, and analytics at scale.
- Implement data pipelines that draw operational and sensor data from core MPA systems such as SG Maritime Data Hub, digitalPORT@SGTM, port operation and vessel traffic information systems, that can be harnessed in data science and AI (DSAI) applications.
- Develop and manage continuous improvement of data architecture and ensure alignment with business requirements, data management and governance policies.
- Participate in the evaluation of strengths and weaknesses of possible technologies and recommend solutions that best meet the organization requirements.
- Design, develop, and maintain interactive dashboards that provide insights and data visualizations to support business decision-making.
- Collaborate closely with business users and the data science team to identify relevant data that can help to achieve business goals, such as analysis to inform policy-making and operation/process streamlining.
- Support the design and definition of the data architecture framework, standards, and principles, including modelling, metadata, privacy, security, reference data and master data
- Assist in the development of data pipelines for large datasets such as operational, sensor or unstructured data to:
- Enable the implementation of DSAI models/applications that support business use cases
- Perform data validation and quality control checks
- Automate regular updating of models and dashboards
- Provide secure access to data via common analytical tools such as Tableau
- Work with the data science team to deploy sophisticated analytics programs, machine learning, and statistical methods, e.g. processing of unstructured input data for automated decision making.
- Identify data processes and tasks that can be automated to increase officer productivity.
- Assist in the compilation and maintenance of an MPA data catalogue to foster awareness of data available to support business use cases.
- Assist in the development of data competencies across MPA to promote a data-driven culture, via workshops and co-development of data products.
- Collaborates with stakeholders to understand business requirements, designs and develops interactive dashboards using data visualization tools, develops and maintains data pipelines, creates and maintains documentation for the dashboards, works with cross-functional teams to ensure data consistency, and stays up-to-date with the latest data visualization techniques.
Requirements
Degree in Data Science, Computer Engineering, Electrical Engineering, Information Systems, or other related disciplines that provide proficiencies in data engineering. Fresh graduates are welcome to apply.
Good coding and scripting capability in Python and SQL.
Familiarity with data management, data architecture, ETL processes (for both structured and unstructured data sources), and building data pipelines using distributed process frameworks, e.g. Cloudera Hadoop.
Knowledge or experience in any of the following areas are a plus
a. Experience in data engineering and data architecture design and implementation, including experience in architecting or developing organizational-level enterprise data lakes or data warehouse solutions.
b. Experience working with medium to large data processing pipelines, distributed data stores and distributed file systems, especially enterprise data platforms and Big Data tools.
c. Experience in cloud platforms used in Government Commercial Cloud, e.g. AWS and Azure
d. Proficient in data visualization tools such as Tableau, Power BI
Creative and innovative in solving problems.
Achievement driven and delivery focused while maintaining required quality.
Team player with strong organisational skills.
Experience in collaborating with interdisciplinary teams that combine technical, business and data science competencies.
Excellent communication skills, both oral and written, with ability to pitch ideas and influence stakeholders.
