Data Engineer

1 week ago

Paya Lebar, Singapore SSG SkillsFuture Singapore Agency Full time

[What you will be working on]

The officer will be required to:

- Manage data pipelines which consist of a series of stages through which data flows (for example, from data sources or endpoints of acquisition to integration and consumption for specific use cases). These data pipelines must be created, maintained and optimised as workloads move from development to production for specific use cases.
- Tap on innovative and modern tools, techniques and architectures to partially or completely automate the most-common, repeatable and tedious data preparation and integration tasks in order to minimize manual and error-prone processes and improve productivity; will also need to assist with implementing the data management infrastructure to drive automation in data integration and management.
- Work with the Data Governance teams to participate in vetting and promoting content created in the business, by data scientists and the curated data catalog, for governed reuse.

[ What we are looking for ]
- Tertiary qualification in computer science, statistics, applied mathematics, data management, information systems, information science or a related quantitative field is required.
- Ideally have a combination of IT skills, data governance skills, and analytics skills with a technical or computer science degree.
- At least six years of work experience in data management disciplines including data integration, modelling, optimization and data quality, and/or other areas directly relevant to data engineering responsibilities and tasks.
- At least three years of experience working in cross-functional teams and collaborating with business stakeholders in support of a departmental and/or multi-departmental data management and analytics initiative in a dynamic business environment.
- Expected to collaborate with both the business and IT teams to define the business problem, refine the requirements, and design and develop data deliverables accordingly. Regular discussions with data consumers on optimally refining the data pipelines developed in nonproduction environments and deploying them in production is also necessary.
- Confident, energetic self-starter, with strong interpersonal skills.
- Good judgment, a sense of urgency and has demonstrated commitment to high standards of ethics, regulatory compliance, customer service and business integrity.

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