Machine Learning Engineer

3 hours ago

Wellington City, New Zealand New Zealand Government Full time

Its an exciting time to be joining The Reserve Bank - Te Pūtea Matua we are investing in new technology and approaches to grow its data capabilities. This role will help assess the suitability of different technologies and methods.
- Join a collaborative and supportive data group
- 5 weeks annual leave, and flexi leave
- Full time, Permanent role; Wellington or Auckland based

Te tūranga - The role and your impactThe of Machine Learning Engineer contributes to the development and maintains the Bank's data solutions including its cloud-based enterprise data platform, various databases and data warehouses, and the associated DevOps/DataOps tools used to support this ecosystem. In this role, you'll get to work on lots of stimulating projects.This is a new role focusing on:

- the technical leader for delivery of MLOps strategies for granular data projects, working efficiently and effectively with large, complex data sets.
- Develop clear DBT pipelines supporting excellent machine learning projects.
- Work with the data experts including architects, analysts, and governance to understand and fulfil the data and information needs of business stakeholders.
- Provide strategic and technical guidance to managers and decision makers within RBNZ on technical and resource considerations

**Ō pūkenga - About youWe're looking for someone who may have**:

- Relevant tertiary level qualification or 5+ years' relevant experience.
- Experience managing and supporting critical, highly available data-based solutions.
- Draws on aspects of data science, data engineering, and specialised machine learning skills.
- Proven experience using, developing and supporting cloud-based database and data warehousing solutions (Azure), Snowflake.
- Good understanding of modern data warehousing (cloud and otherwise) including data lake and dash mesh patterns.
- Experience in database design, modelling, processes and standards.
- Extensive knowledge of the SDLC and contemporary tools and practices developing and releasing data pipelines (including using distributed source control such as git)
- Good working knowledge of Azure, Snowflake, DBT, SQL and Microsoft SQL Integration, programming skills in a language commonly used to manipulate data such as Python or R
- A growth mindset

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