Build scalable pipelines and models using Snowflake and dbt in a high-growth, cloud-native team focused on AI and analytics.
Data Engineer | High-Growth Cloud-Native Environment
Why You’d Like It
If you are a Data Engineer who thrives on the "modelling" side of the house as much as the "engineering" side, this is the challenge you’ve been looking for. You will be stepping into a cloud-native environment where your work directly transforms raw data into high-value assets for decision-making. It’s the perfect blend of technical depth and tangible impact, working with a modern stack in a team that actually values automation and quality over quick-and-dirty fixes.
The Story
The business is currently in a "high growth" phase, which has triggered a significant investment in their data platform. They are moving beyond simple reporting to build a sophisticated, scalable analytics engine. Because they are expanding rapidly, they need an engineer who can handle the pace of an innovative product development environment and take ownership of complex datasets to support new directions in AI and analytics.
Company Profile
Based in Auckland, this is a globally recognised leader in fleet management and technology solutions. They are a tech-first organisation that prides itself on being "cloud-native," leveraging both AWS and Azure to power their platform. The culture is built on being pragmatic, collaborative, and ambitious, with a strong emphasis on doing what's right for the customer.
Your Role
Working under the guidance of the Analytics & AI Lead, you will be responsible for the "plumbing" and the "logic" of the data ecosystem. Your day-to-day will involve:
We are looking for a seasoned engineer who is comfortable working across the full data lifecycle. To hit the ground running, you’ll need:
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.
Why You’d Like It
If you are a Data Engineer who thrives on the "modelling" side of the house as much as the "engineering" side, this is the challenge you’ve been looking for. You will be stepping into a cloud-native environment where your work directly transforms raw data into high-value assets for decision-making. It’s the perfect blend of technical depth and tangible impact, working with a modern stack in a team that actually values automation and quality over quick-and-dirty fixes.
The Story
The business is currently in a "high growth" phase, which has triggered a significant investment in their data platform. They are moving beyond simple reporting to build a sophisticated, scalable analytics engine. Because they are expanding rapidly, they need an engineer who can handle the pace of an innovative product development environment and take ownership of complex datasets to support new directions in AI and analytics.
Company Profile
Based in Auckland, this is a globally recognised leader in fleet management and technology solutions. They are a tech-first organisation that prides itself on being "cloud-native," leveraging both AWS and Azure to power their platform. The culture is built on being pragmatic, collaborative, and ambitious, with a strong emphasis on doing what's right for the customer.
Your Role
Working under the guidance of the Analytics & AI Lead, you will be responsible for the "plumbing" and the "logic" of the data ecosystem. Your day-to-day will involve:
- Designing, building, and optimising data pipelines for ingestion and transformation across streaming, batch, and API sources.
- Developing and maintaining dimensional models (star schemas) to ensure data is structured for high-performance analytics.
- Collaborating with cross-functional teams to implement CI/CD automation, data lineage, and governance.
- Using Infrastructure as Code (Terraform) to manage and provision cloud resources.
- Monitoring and troubleshooting production workflows to ensure the platform remains resilient and meets SLAs.
We are looking for a seasoned engineer who is comfortable working across the full data lifecycle. To hit the ground running, you’ll need:
- Dedicated experience in Data Engineering.
- Solid experience in Java would be benificial and a proven track record of supporting cloud-native applications.
- Advanced SQL skills and deep experience with modern data warehouses—ideally Snowflake and dbt.
- Hands-on experience with streaming and batch frameworks like Kinesis, Glue, Kafka, or Azure Data Factory.
- A proactive mindset regarding data quality and a history of working with Git-based workflows and CI/CD pipelines.
- The ability to chat with both techies and non-technical stakeholders to turn business requirements into smart technical solutions.
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