Databricks Consultant / Engineer

Overview

This opportunity is for a Databricks specialist who can work closely with clients and delivery teams to build, improve, and govern modern data platforms. The role spans data engineering, governance, automation, and quality engineering, with a strong emphasis on Databricks, Delta Live Tables, and related cloud tooling. There are three openings across different organisations: two onsite positions and one hybrid position in New Zealand.

Important Requirement

A current Databricks certification is mandatory for this position. You must also bring strong client-facing experience along with hands-on expertise in Databricks and Delta Live Tables (DLT).

What You Will Do

• Improve and scale the Databricks platform so it supports secure, enterprise-ready data solutions.
• Build and maintain governance structures, including catalogs and metadata management practices.
• Work with Databricks capabilities and associated services such as Delta Live Tables and Lakeflow connections.
• Apply data modelling techniques for both analytical and operational use cases, including star and snowflake structures.
• Develop and support infrastructure-as-code approaches for Databricks environments.
• Partner with stakeholders to turn business needs into governed, reusable data products.
• Enforce source control practices using platforms such as Git or Azure DevOps.
• Create, manage, and improve CI/CD pipelines and environment management workflows for data engineering delivery.
• Introduce automated testing and data validation for data pipelines.
• Carry out performance testing and tuning for data engineering solutions.
• Write, review, and maintain unit and integration tests to raise solution reliability.
• Record issues and fixes clearly for review and future reference.
• Oversee testing activities to confirm data accuracy, performance, and overall quality.
• Support the ongoing improvement and sharing of internal frameworks and templates.

Requirements

• Bachelor's or Master's degree in Computer Science, Data Engineering, or comparable practical experience.
• Strong working knowledge of Python, SQL, and Terraform or a similar infrastructure-as-code tool.
• Demonstrated depth in Databricks, including Delta Lake and Unity Catalog.
• Hands-on experience with infrastructure as code, automation, and CI/CD pipelines.
• Working knowledge of cloud technologies, with AWS preferred.
• Ability to model both structured and unstructured data effectively.
• Client-facing communication and consulting experience.
• Comfort with a proactive, determined, and resilient work style.
• Fabric experience is an advantage.
• Exposure to high-throughput data processing pipelines is beneficial.
• Experience with data visualisation tools is a plus.

Additional Information

The role is full-time and onsite for two of the openings, while one opening is hybrid. The location is New Zealand. No salary information, start date, or application deadline was provided.

Qualifications and Skills Summary

Successful candidates should combine platform engineering, data governance, cloud engineering, and quality assurance capability, with the ability to collaborate effectively with stakeholders and deliver robust, secure data solutions.