Domain lead - Data Engineering
Foodstuffs is hiring a Domain lead - Data Engineering in Auckland, New Zealand. Level rates it ; you can apply on Foodstuffs.
Level's read on this job
- On Level's scale, this data engineer role is Little AI ●○○○: aI is not part of the work.
- Level classes it as a lead role.
- Foodstuffs has 16 other open roles on Level.
- Posted in the last few days.
AI in this role
Ko wai mātou – About us
Kia ora. We’re Foodies. You know New World, PAK’nSAVE and Four Square right? That’s us!
With 300+ stores and over 27,000 Foodies across Te Ika-a-Maui, our North Island Co-op has the privilege of helping New Zealanders get more out of life. Locally owned, we reflect the communities we serve, and we celebrate our people - our taonga, every day for being uniquely them.
Our Support Centre is 1,500+ people strong, which includes 500+ IT employees, who all play a vital role in ensuring the cogs of our Co-op stay turning and our systems stay ‘byte’-sized and ‘bug’-free.”.
Te Tūranga – About the role
We’re looking for an experienced Domain Lead for Data Engineering to lead the engineering direction, strategy and capability of our Data domain.
This is a senior leadership role with the opportunity to influence how data is engineered, governed, shared and consumed across the organisation. You’ll work across Data Engineering, Architecture, Analytics, Data Governance and our business domains to create a trusted, scalable and sustainable data ecosystem.
You’ll lead through Principal Engineers, Tech Leads, and Chapter Leads setting clear direction and enabling our technical leaders and teams to turn that direction into great engineering outcomes.
What you’ll do
- Set the direction for modern data engineering, establishing practical standards, guardrails, patterns and reference architectures across the domain.
- Lead through technical leaders, empowering Principal Engineers, Tech Leads, and Chapter Leads to shape the technical detail while maintaining clear accountability for domain outcomes.
- Champion data-as-a-product, enabling teams to create data that is trusted, reusable, discoverable, well governed and valuable to the business.
- Drive modern data engineering practices, including DataOps, automation, CI/CD, data quality, observability, metadata and lineage.
- Shape our approach to modern data platforms, including cloud data platforms, lakehouse, data fabric, data mesh, semantic modelling and governed self-service analytics.
- Balance autonomy with consistency, giving teams room to innovate while ensuring enterprise standards for security, quality, governance and engineering are maintained.
- Build and develop our Data engineering capability, strengthening technical leadership, career pathways, communities of practice and succession across the domain.
Ngā painga - What we offer
We’re committed to providing awesome experiences for our people, including offering a range of benefits
- Inhouse learning and development programmes and courses, flu vaccinations, and social network groups (we call them Tribes).
- Flexible working options, a day off on your birthday, long service leave
- Free carparking - we’ve got over 1,000 carparks including EV plugs
- Onsite café with subsidised meals, mini mart, 5% discount at our retail stores
He kōrero mōu - About you
- Significant leadership experience across enterprise-scale data engineering, data platforms, analytics engineering or data architecture.
- Deep understanding of modern data architecture and engineering, including cloud data platforms, data warehouses, data lakes/lakehouse, data fabric, data mesh and modern integration patterns.
- Strong experience establishing data engineering standards, patterns and guardrails that improve quality, security and consistency without creating unnecessary barriers for delivery teams.
- Strong experience with data-as-a-product, including building trusted, governed, discoverable and reusable data assets for enterprise use.
- Experience improving engineering maturity across data quality, DataOps, CI/CD, pipeline reliability, observability, metadata and security-by-design.
- A strong understanding of data governance, privacy, lineage, ownership and data quality, and how these work alongside engineering to create trust in data.
- Experience working with enterprise data and analytics technologies such as Google BigQuery or equivalent cloud data platforms, SAP Datasphere, Power BI, SAP Analytics Cloud, data orchestration and integration technologies.
- Proven ability to balance engineering excellence, business value, governance, commercial realities and long-term platform sustainability.
- Experience supporting the strategic direction, health and investment of enterprise data platforms, including lifecycle management, scalability and cost optimisation.
Experience awesome. Achieve awesome. Be awesomely you.
We’re proud to have a focus on Diversity & Inclusion here at Foodies and welcome courageous behaviour, encourage togetherness, inspire our people to be their best selves in our Foodies whānau.
We encourage you to apply with all your awesomeness and welcome your diverse background, including any disability, additional health and mental health needs, and/or neurodiversity.
If you require accessibility support to ensure you can fairly access our recruitment process, please reach out to Recruitment.Foodstuffs@foodstuffs.co.nz. Accessibility support could include, interview location, sign language interpreter, assistive technology.
Don’t ‘cart’ around – apply now!
Are you ready to be part of our bunch – apply now!
How we rate this
Domain lead - Data Engineering at Foodstuffs rates 22 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
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Pay
- Typical data engineer job
- $146k
This posting doesn't list pay. Use the typical data engineer figure when pay comes up. See data engineer jobs
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