[What the role is]
You will be a key member of the Data & AI Engineering team.[What you will be working on]
1. 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.
2. Support the design and definition of the data architecture framework, standards, and principles, including modelling, metadata, privacy, security, reference data and master data.
3. Assist in the development of data pipelines for large datasets such as operational, sensor or unstructured data to:
4. Identify data processes and tasks that can be automated to increase officer productivity.
5. Assist in the compilation and maintenance of the data catalogue to foster awareness of data available to support business use cases.
6. Assist in the development of data competencies to promote a data-driven culture, via workshops and co-development of data products.
7. 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.
[What we are looking for]
1. Background in Data Science, Computer Engineering, Electrical Engineering, Information Systems, or other related disciplines that provide proficiencies in data engineering.
2. Good coding and scripting capability in Python and SQL.
3. 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.
4. Knowledge or experience in any of the following areas are a plus:
5. Creative and innovative in solving problems.
6. Achievement driven and delivery focused while maintaining required quality.
7. Team player with strong organisational skills.
8. Experience in collaborating with interdisciplinary teams that combine technical, business and data science competencies.
9. Excellent communication skills, both oral and written, with ability to pitch ideas and influence stakeholders.