Analytics & Visualization Engineer: Dashboards & Data Pipelines

PHF Science; Auckland, Wellington, Christchurch; Remote; NZD 90,000 - 130,000; Full time

Benefits offered by this job

Flexible working options

4 weeks annual leave + 2 days + PHF-Sc

15 days sick leave

Volunteer day

Flu vaccinations

Insurance discounts

EAP access

Job summary

PHF Science in New Zealand is seeking an Analytics and Visualisation Engineer for a fixed-term role through 31 March 2027. You will develop scalable ETL pipelines, API integrations, and GIS-enabled visualisations to support public health dashboards and data pipelines.

You will collaborate with PHF Science experts to turn complex datasets into actionable insights, define analytics standards, and identify opportunities for service improvement while enjoying flexible work arrangements across

Qualifications

• Experience in an analytics role delivering dashboards and data pipelines.
• Relevant tertiary qualification in CS/IT/Data Eng or related.
• Strong coding experience in R, Python, SQL and BI tools.
• Excellent communication and problem-solving skills.

Responsibilities

• Develop scalable data ETL pipelines and API integrations.
• Support exploitation of diverse datasets and GIS-enabled visualisations.
• Prepare near-real-time data collection, ingestion, storage and analysis solutions.
• Develop analytics app deployment standards and best practices.
• Gather requirements and drive continuous service improvement.

Skills

Analytics experience

Numerical skills

Problem solving

Communication skills

Cross-cultural communication

Education

Tertiary qualification in CS/IT/Data Eng

Tools

R

Python

R Shiny

Tableau

PowerBI

T-SQL

Snowflake

Job description

PHF Science in New Zealand is seeking an Analytics and Visualisation Engineer for a fixed-term role through 31 March 2027. You will develop scalable ETL pipelines, API integrations, and GIS-enabled visualisations to support public health dashboards and data pipelines.

You will collaborate with PHF Science experts to turn complex datasets into actionable insights, define analytics standards, and identify opportunities for service improvement while enjoying flexible work arrangements across