Lead Analytics Engineer

Are you the engineer clients trust when the build has to work? And the leader your team turns to when the problem gets hard? We’d love to talk.

Data Insight is growing, and we need a Lead Analytics Engineer to help shape our engineering and analytics engineering practice. You’ll report to our Director – Delivery & AI. You’ll coach a team of engineers, own delivery on client projects, and set the engineering standards everyone else works to.

This isn’t a role where you hand off the build and step back. You’ll scope, design and build modern data platforms, then turn them into analytics clients actually use in production. When the hardest technical problem on a project shows up, it lands with you, and you’ll help your team learn how to solve the next one.

What you’ll be doing

• Leading data and analytics engineering engagements end to end, from scoping and estimation through build, QA and handover


• Getting hands-on when it counts: designing and building scalable pipelines, lakehouse solutions and data models, with Databricks at the core alongside Azure, AWS and Fabric


• Turning engineered data into semantic models, dashboards and insights that drive real decisions


• Setting the bar on engineering standards, including code review, testing, CI/CD, Infrastructure as Code, data quality and documentation


• Leading, mentoring and growing a team of data engineers and analytics engineers, and helping hire and onboard as the team grows


• Managing scope, budgets and timelines, and building trusted relationships with senior client stakeholders


• Working with our sales and leadership teams on RFPs, proposals and solution design, and spotting new opportunities within existing accounts


• Helping shape our practice strategy, service offerings and partnerships with Databricks and Microsoft

What you’ll bring

• 7+ years in data engineering, analytics engineering or related roles, including 2+ years leading technical teams while staying hands-on


• Consultancy or professional services experience across multiple clients is highly desirable


• Strong, recent Databricks experience across Spark/PySpark, Delta Lake, Unity Catalog and Workflows


• Advanced SQL and Python, plus solid data modelling skills: dimensional modelling, SCDs and medallion architecture


• Experience building production pipelines with tools like Azure Data Factory, Airflow, AWS Glue or dbt


• Experience with version control, CI/CD, automated testing and Infrastructure as Code (e.g. Terraform)


• Broader cloud experience (Azure, AWS or GCP) and familiarity with Snowflake and Fabric


• Experience with at least one visualisation tool (e.g. Power BI, Tableau) and the ability to take data all the way through to insight


• A track record of leading project delivery end to end, covering scoping, budgets, timelines and stakeholders


• A commercial mindset. You always ask “so what?”

Bonus points for: a Databricks certification (e.g. Data Engineer Professional), data governance tooling such as Unity Catalog or Purview, streaming experience (Kafka, Event Hubs, Structured Streaming), and a feel for where AI and ML create real business value.

Why Data Insight?

Since 2013, we’ve been the go-to partner for organisations navigating their data journeys, covering everything from data strategy to AI. Here’s what you get:

• Work alongside some of NZ’s leading data and analytics experts across a wide range of clients and tech environments


• Agency energy without the bureaucracy


• Flexible hours and hybrid working


• Real career and development opportunities


• An active (and fun) social club

See why our team loves it here: https://www.datainsight.co.nz/careers

Ready to lead? We’re reviewing CVs as they arrive and interviewing as we go, so apply now. You’ll need NZ work rights, and ideally be based in NZ.