(Senior) Data Engineering Lead

About Auror At Auror, we’re empowering the retail industry to tackle theft and Organised Retail Crime, a $150 Billion problem globally. It’s high volume crime that’s increasingly organised in nature and is putting people, retailers, and communities at risk every day. Founded in New Zealand 13 years ago, we’re working with some of the best and largest retailers in the world across the US, Canada, Australia, New Zealand, and the UK.Auror is connecting people and intelligence to reduce crime. We’re using technology for good. In partnership with our leading retail partners, we need people with the passion, determination, and innovation required to overcome one of the world's largest problems. If you’re looking to make a difference with and for the people dedicated to stopping crime, for good, then we want you on our team. We're also embracing the potential of AI to supercharge our impact—whether that's enhancing the way we detect trends, support our customers, or improve internal workflows. As a company, we're committed to responsibly incorporating AI into how we work and what we build, and we encourage all Aurors to be curious about how AI can elevate their work, regardless of role or function. The Role As a Data Engineering Lead, you’ll scale the data foundations that help Auror achieve its mission: reducing violent retail crime by 50% in five years. You’ll lead the technical direction and day-to-day delivery of our data engineering team — building the scalable, observable, and trusted data platform that powers our products, insights, and AI capabilities. This is a role for someone who loves both building and leading. You’ll stay close to the code while raising the technical bar, coaching engineers to do their best work, and partnering across Data & AI, Product, Engineering and Platform to turn complex data challenges into real-world impact. Success means more than shipping pipelines and infrastructure. It means building a team that delivers with confidence, creating data products people can rely on, and ensuring Auror has the trusted data foundation it needs to help retailers, law enforcement, and communities prevent harm, act faster, and make safer decisions. Practically this will involve: Technical Leadership & Delivery - Lead the design and delivery of scalable, reliable, and observable data platforms, pipelines, and consumption models using technologies such as Dagster, Airflow, dbt, Apache Iceberg, Cloud Spanner, and BigQuery. Design and evolve data models that enable trusted, well governed, and high performance analytics and operational use cases. - Partner closely with software engineering teams to design data models and integration patterns that support new product capabilities, ensuring data is modelled for both operational and analytical consumption from the outset. - Own and evolve data infrastructure across Azure, Google Cloud Platform (GCP), Snowflake, and Terraform, ensuring infrastructure is reusable, secure, well governed, and resilient. - Drive continuous improvements in data quality, reliability, and observability by identifying the largest sources of operational toil and rework, then delivering measurable outcomes. - Review high risk technical designs and production changes, ensuring solutions are observable, thoroughly tested, rollback ready, and maintainable before release. - Manage the full lifecycle of data assets, including metadata, logging, retention policies, and access governance, ensuring the platform remains secure, compliant, and scalable. People Leadership - Build and support a high-performing team of data engineers, setting clear expectations, providing regular and actionable feedback, and creating growth plans aligned to individual strengths and business needs. - Build a learning-oriented team culture by modelling openness to feedback, creating clarity during uncertainty, and helping team members reframe challenges as opportunities to grow. - Apply pay, promotio