Lead Analytics Engineer — Hybrid Data Platform Leader

Data Insight; Auckland; Hybrid; NZD 140,000 - 210,000; Full time

Benefits offered by this job

Hybrid working

Career development

Flexible hours

Job summary

Data Insight in Auckland seeks a Lead Analytics Engineer to shape our engineering and analytics practice. You will coach a team, own delivery on client projects, and set engineering standards. You’ll design, build, and scale data platforms, turning data into insights used in production.

You will lead end-to-end engagements, mentor engineers, and work with senior stakeholders, Databricks, Azure, AWS and Fabric to solve complex problems and grow the team.

Qualifications

• 7+ years in data engineering or analytics engineering roles, with leadership experience.
• Consultancy or professional services exposure across multiple clients is desirable.
• Strong Databricks experience including Spark/PySpark and Delta Lake.
• Advanced SQL and Python with solid data modelling skills (dimensional modelling, SCDs).
• Experience building production pipelines with Azure Data Factory, Airflow, AWS Glue or dbt.

Responsibilities

• Lead data and analytics engineering engagements end to end, from scoping to handover.
• Design and build scalable pipelines, lakehouse solutions and data models with Databricks at the core.
• Turn engineered data into semantic models, dashboards and actionable insights.
• Set engineering standards: code review, testing, CI/CD, IaC, data quality and docs.
• Mentor and grow a team of data engineers and analytics engineers; participate in hiring.

Skills

Data engineering

Analytics engineering

Team leadership

Databricks

SQL

Python

Data modelling

CI/CD

Terraform

Azure

AWS

GCP

Power BI

Tableau

Tools

Databricks

Azure

AWS

dbt

Airflow

Power BI

Tableau

Terraform

Job description

Data Insight in Auckland seeks a Lead Analytics Engineer to shape our engineering and analytics practice. You will coach a team, own delivery on client projects, and set engineering standards. You’ll design, build, and scale data platforms, turning data into insights used in production.

You will lead end-to-end engagements, mentor engineers, and work with senior stakeholders, Databricks, Azure, AWS and Fabric to solve complex problems and grow the team.