Principal Engineer

5 days ago

Singapore MPA Maritime and Port Authority of Singapore Full time

[What the role is]

Undertake the functions of Principal Engineer in the Statistics & Data Systems (SDS) department to support the collection, storage and analysis of data in a scalable, repeatable and secure manner.

[What you will be working on]
- Lead the planning, stakeholder engagement, development, implementation and maintenance of systems for data collection, storage, access, and analytics at scale.
- Work with system architects and the core data engineering team to ensure the data architecture aligns with business requirements, data management and governance policies.
- Serve as internal consultant to departments on data engineering best practices.
- Profile MPA’s DSAI capabilities and initiatives to gain mindshare within the government and industry.
- 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.
- Develop data pipelines large datasets such as operational, sensor or unstructured data to:

- 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.
- Compile and maintain an MPA data catalogue to foster awareness of data available to support business use cases.
- Develop data competencies across MPA to promote a data-driven culture, via workshops and co-development of data products.

[What we are looking for]
- Background in Data Science, Computer Engineering, Information Systems, Business Analytics, or other related disciplines that provide proficiencies in data engineering or data science.
- At least 5 years’ of experience in data engineering and data architecture design and implementation. Experience in architecting or developing an enterprise data lake or data warehouse solution is a plus.
- Strong competency in building data pipelines using distributed process frameworks, e.g. Cloudera Hadoop.
- Strong coding and scripting capability, e.g. expertise in Python/R/SQL.
- Strong knowledge and expertise on data management, data architecture, ETL processes (for both structured and unstructured data sources).
- Knowledge or experience in any of the following areas are a plus:

- Experience working with medium to large data processing pipelines, distributed data stores and distributed file systems, especially enterprise data platforms and Big Data tools.
- Experience in cloud platforms used in Government Commercial Cloud, e.g. AWS and Azure
- Understand business processes well.
- Creative and innovative in solving problems.
- Achievement driven and delivery focused while maintaining required quality.
- Team player with strong organisational and people management 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.

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