Senior Data Engineer / Consultant - Databricks

ABOUT ADAPTIV

Adaptiv is a Kiwi success story specialising in Integration, Data, AI and Cloud Consulting. We help organisations unlock greater value from their data through modern integration and analytics solutions built on technologies including Databricks, Microsoft Azure, Microsoft Fabric, MuleSoft, Boomi and Solace.

Based in our Grey Lynn/Ponsonby offices, we offer a collaborative, people-first culture where curiosity, initiative and continuous learning are valued. We combine strong technical capability with a practical, down-to-earth approach and are looking for people who share that mindset.

We are ideally seeking candidates based in Auckland. We will also consider people located in Christchurch, Wellington or elsewhere in New Zealand who are able to travel when required.

ABOUT THE ROLE

We are looking for experienced Senior Data Engineers / Consultants to join our growing Data Practice.

These are hands-on consulting roles focused on delivering modern Databricks and Azure-based data solutions across a variety of client environments. You will work closely with clients, architects and delivery teams to design, build, deploy and optimise scalable data platforms that deliver meaningful business outcomes.

Success in this role requires strong engineering capability together with the confidence to engage directly with stakeholders, understand business requirements and translate them into practical, supportable data solutions.

As a senior member of the team, you will also contribute to solution design, mentor other engineers and help strengthen the frameworks, standards and reusable delivery practices supporting Adaptiv’s continued growth.

WHAT YOU’LL BE DOING

• Design, build and optimise production data pipelines across Lakehouse and data warehouse environments.

• Develop high-quality data transformations using Python, PySpark and SQL for analytics, reporting and AI/ML workloads.

• Deliver solutions using Azure Databricks, Delta Lake, notebooks, workflows and Medallion Architecture.

• Work with Lakeflow Spark Declarative Pipelines, formerly Delta Live Tables, where appropriate.

• Implement governance and security practices using capabilities such as Unity Catalog.

• Build and maintain automated deployment processes using Git, Databricks Asset Bundles and CI/CD pipelines.

• Work with orchestration technologies such as Databricks Workflows, Azure Data Factory or Apache Airflow.

• Implement automated testing, monitoring, data-quality and operational-support practices.