Data Engineering Lead

  • New Zealand
  • Auckland
  • Permanent
  • Highly attractive benefits

They are building an enablement-led Data, Insights & AI function that will provide trusted enterprise data foundations, governed analytics, safe AI capability and self-service enablement across the business.
This role will own the engineering platform that underpins every downstream analytics, reporting and AI capability.
This is a hands-on technical leadership role. You’ll remain close to the platform, designing pipelines, reviewing code, improving reliability and solving production issues while setting the standards, operating rhythm and engineering discipline that allow a small but growing team to scale safely.

Required Skills:

  • Significant hands-on experience operating production data platforms, ideally including Databricks, Spark, Delta Lake and Unity Catalog, or equivalent cloud-native data platforms such as Azure Synapse, Snowflake or AWS data services
  • Strong experience across ingestion, transformation, orchestration, deployment and operational support of enterprise data platforms
  • Proven experience designing and scaling medallion-style data architectures across bronze, silver and gold layers, or equivalent layered data modelling patterns
  • Strong Python and SQL skills
  • Comfortable working with CI/CD, GitHub or Azure DevOps, version control and modern engineering workflows
  • Experience setting engineering standards across ingestion, transformation, testing, observability, deployment and code review
  • Strong understanding of platform reliability, including SLAs, incident response, runbooks, monitoring and post-incident improvement
  • Experience leading small but growing technical teams with a coaching-led, hands-on leadership style
  • Ability to review technical designs, challenge trade-offs and act as the technical authority for the data platform
  • Strong stakeholder management skills, with the ability to communicate clearly with both technical and non-technical audiences
  • Commercial awareness around platform cost, cloud usage, workload right-sizing and cost transparency

Nice to Have Skills:

  • Experience working in financial services or another regulated environment
  • Exposure to FinOps practices for cloud data platforms, particularly Azure or Databricks
  • Familiarity with AI/ML production platform patterns such as MLflow, model registry or feature stores
  • Experience with data product thinking, data contracts and certified datasets
  • Experience working closely with analytics, governance, architecture, information security and risk teams
  • Databricks, Azure, data engineering or cloud certifications

This is a fantastic opportunity to take ownership of a critical data platform where your technical leadership will have genuine visibility and impact.

You’ll suit this role if you are a builder at heart: someone who enjoys hands-on platform craft, develops engineers through the way work is done, and knows how to create standards that are practical, adopted and useful.

For a confidential chat, apply with an updated CV to JP Browne.

Apply now

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