Data Engineer - SMARTLY

About Smartly

Smartly, part of Datacom, helps New Zealand businesses manage payroll with less hassle. The platform supports more than 20,000 businesses and is designed to ensure people are paid accurately, on time, and in compliance with relevant legislation. As a growing fintech business expanding into related markets, Smartly offers a lively, fast-moving workplace with strong opportunities to learn and progress.

Role Overview

Smartly is hiring a Data Engineer to design, support, and improve the data pipelines and datasets that enable analytics and business decisions. In this position, you will partner with Data Science, Analytics, Product, and Engineering teams to keep data dependable, well-organised, and straightforward to work with.

This opportunity suits someone who enjoys practical data work using SQL and Python, and who is comfortable working in a modern software engineering environment. You will contribute to the evolution of the data platform while building capability in cloud-based data systems and engineering best practices.

Smartly also uses AI-assisted development tools as part of its workflow. Prior expert-level experience is not required, but you should be open to using or learning tools such as Cursor, GitHub Copilot, or similar to speed up coding, testing, and troubleshooting.

The team views AI as an important part of modern data and software engineering and values people who are curious, practical, and willing to adapt their working methods.

What You’ll Do

• Create, maintain, and improve data pipelines with SQL and Python to ingest, transform, and deliver data from core product systems and external sources.
• Build and maintain well-structured analytical datasets that support reporting, dashboards, experimentation, and data science needs.
• Work with analysts and data scientists to understand data needs and turn them into dependable, reusable data assets.
• Track pipeline and dataset health, and investigate and fix data quality or reliability problems.
• Help improve documentation, testing, and basic observability so the wider business can trust and use the data more easily.
• Contribute to better data tools, stronger pipelines, and improved development practices across Smartly.
• Operate in a cloud environment with a practical understanding of how cloud-based data systems function.

Requirements

• At least 3 years of experience in data engineering, analytics engineering, or a closely related role.
• Strong SQL capability, including the ability to write complex and efficient queries.
• Strong Python ability, especially for transformation logic, automation, and pipeline development.
• Experience using Git or a comparable version control tool in a team setting.
• Familiarity with CI/CD workflows, including automated testing and deployment.
• Working knowledge of cloud infrastructure concepts such as compute, storage, and permissions, ideally in a modern cloud platform.
• Experience with relational databases and analytical data stores.
• Understanding of analytics data modelling, including fact and dimension table concepts.
• Comfort working independently on data tasks end-to-end, with suitable support when needed.
• Ability to collaborate effectively with analysts, data scientists, and software engineers.
• Curiosity and initiative, especially when it comes to improving data quality and engineering practices.
• Strong communication skills, with the ability to explain data issues and solutions to both technical and non-technical audiences.

Perks and Work Environment

• Flexible working options, including the ability to split time between home and the offices in Lower Hutt or Auckland CBD.
• A strong company culture with events such as a big morning tea, work celebrations, and casual shared lunches.
• A people-focused environment that supports growth and helps employees thrive.

Application Instructions

Applicants are asked to submit a cover letter and CV using the application process provided.

If you believe this role matches your background and interests, you are encouraged to apply.

Additional Information

This is a full-time role based onsite in Auckland, New Zealand, with flexibility to work from home as part of the working arrangement.