Work with one of New Zealands premium employers, further your career as a Data Engineer.
Why You’d Like It
This is a rare opportunity to sit at the absolute cutting edge of data theory and generative AI. You will move beyond traditional manual pipeline construction to build next-generation infrastructure where dimensional modeling meets agentic coding frameworks, allowing you to automate code execution and self-healing loops.
The Story
The data landscape is shifting rapidly, and this team is leading the charge by unlocking the power of data to completely reimagine the retail landscape. To support a major evolution in how data is consumed across the business, there is a focus on building clean, predictable data environments. This has created a need for a forward-thinking engineer who can bridge the gap between core data engineering and autonomous AI capabilities.
Company Profile
Operating as a high-performing, innovative hub within a well-established household brand, this group acts as the predictive engine for the wider business. They focus on turning massive datasets into smart, everyday solutions that make people's lives a little better. With a modern cloud setup and a collaborative, agile culture, they provide the stability of a large enterprise alongside the speed and experimentation of a tech startup.
Your Role
As a Data/AI/ML Engineer, your core mission is to implement clean data environments that serve as the foundation for everyone from business analysts to autonomous AI agents.
Key responsibilities include:
The ideal candidate brings a strong foundation in core software discipline alongside a demonstrable pivot into GenAI automation.
To thrive in this role, you should have:
Does this sound like it could be the next role for you? Get in touch with Dan for a confidential discussion email [email protected] or call on 021331559
This is a rare opportunity to sit at the absolute cutting edge of data theory and generative AI. You will move beyond traditional manual pipeline construction to build next-generation infrastructure where dimensional modeling meets agentic coding frameworks, allowing you to automate code execution and self-healing loops.
The Story
The data landscape is shifting rapidly, and this team is leading the charge by unlocking the power of data to completely reimagine the retail landscape. To support a major evolution in how data is consumed across the business, there is a focus on building clean, predictable data environments. This has created a need for a forward-thinking engineer who can bridge the gap between core data engineering and autonomous AI capabilities.
Company Profile
Operating as a high-performing, innovative hub within a well-established household brand, this group acts as the predictive engine for the wider business. They focus on turning massive datasets into smart, everyday solutions that make people's lives a little better. With a modern cloud setup and a collaborative, agile culture, they provide the stability of a large enterprise alongside the speed and experimentation of a tech startup.
Your Role
As a Data/AI/ML Engineer, your core mission is to implement clean data environments that serve as the foundation for everyone from business analysts to autonomous AI agents.
Key responsibilities include:
- Designing and maintaining scalable data architectures using dimensional modeling principles (star schemas, conformed dimensions) across a modern cloud data warehouse.
- Building reliable ingestion pipelines, writing clean modular SQL transformations, and orchestrating workflows from raw ingest to analytics-ready products.
- Acting as the technical owner of the New Zealand Google Cloud Platform (GCP) environment and GitHub organisation.
- Provisioning and managing infrastructure as code (IaC) across all environments covering compute, storage, messaging, IAM, and ML infrastructure.
- Integrating production-grade AI tools (like Claude Code and GitHub Copilot) into day-to-day data engineering workflows to accelerate development.
- Building data products and APIs that enable conversational interfaces and autonomous agents to easily discover and query the data platform.
- Owning data quality from source to consumption through automated testing, CI/CD gates, monitoring, and robust AI guardrails.
The ideal candidate brings a strong foundation in core software discipline alongside a demonstrable pivot into GenAI automation.
To thrive in this role, you should have:
- 3 to 5 years of core data engineering experience with highly proficient SQL skills (query performance, partitioning) and deep knowledge of Python.
- Solid data modeling fundamentals, including relational database design, dimensional modeling (Facts, Dimensions, SCDs), and data warehousing principles.
- Familiarity with modern data tools and cloud environments, specifically GCP/BigQuery, dbt, Airflow, Git, and CI/CD pipelines.
- Practical AI engineering experience working with agentic workflows or developer-facing coding assistants beyond basic prompt engineering.
- A track record of shipping AI capabilities, such as building, experimenting with, or deploying autonomous tools or multi-agent automation scripts.
- A pragmatic approach to problem-solving, a highly collaborative mindset, and the ability to explain complex technical topics to non-technical stakeholders.
- An understanding of statistical modeling, machine learning techniques, and distributed systems concepts for large-scale training/inference (highly regarded).
- Flexible Hybrid Framework: A balanced hybrid working model based out of the Ponsonby and Favona support offices (minimum 3 days a week in office).
- Cutting-Edge Tech Stack: Direct ownership of a modern GCP cloud ecosystem with the freedom to pilot and embed advanced agentic frameworks.
- Career Progression: A clear '3L' engineering career stream offering immense technical growth without the immediate overhead of direct reports.
Does this sound like it could be the next role for you? Get in touch with Dan for a confidential discussion email [email protected] or call on 021331559
Like the sound of that?
If this sounds like you please reach out to me at
dan@digitalgarage.co.nz
dan@digitalgarage.co.nz