About The Team
At Quantaco, we deliver state-of-the-art predictive financial data services for the Australian hospitality industry. We are the eighth-fastest growing company in Australia as judged by the country's flagship financial newspaper, The Australian Financial Review. The Quantaco Technology team is forward-thinking and dedicated to leveraging data to drive innovation and deliver cutting-edge solutions, continuing to accelerate through hyper-automation.
Our engineers are thought leaders in the business and provide significant input into the design and direction of our technology. Our engineering roles are not singular in focus — you will develop new data models, ensure pipelines are fully automated, and run them with bullet-proof reliability. We are a friendly and collaborative team, working with a mature, design-first development process focused on delivering features that enhance our customers experience and improve their bottom line. You'll always be learning at Quantaco.
About The Role & Responsibilities
The Senior Data Engineer is a key role in realising our vision for new and valuable data products and services. You will design, develop, and maintain robust data pipelines and platforms that enable the creation and deployment of those products. At the core, this is a
Python and SQL role — managing data pipelines across multiple domains including financial, payroll, point-of-sale, marketing, and purchase analytics. Your eye for intuitive, simple design, combined with mature data engineering skills and a strong work ethic, will position you well for a rewarding career with Quantaco.
You will work across two primary data platforms — the
Google Cloud platform and
Databricks — within a
multi-cloud architecture, building
dbt-led ETL pipelines and increasingly supporting AI-agentic workflows and knowledge graphs / semantic layers. The opportunities to learn and grow here are limitless: we need you to help identify and make intuitive new data insights that help our customers raise the bar, optimise, and grow their businesses.
Design and development
- Architect, build, and optimise scalable data pipelines and workflows supporting data across financial, payroll, point-of-sale, marketing, and purchase analytics domains.
- Develop data models and schemas that facilitate seamless integration with downstream analytics and applications.
- Build and operate pipelines across two core platforms — GCP Gemini Enterprise and Databricks — within a multi-cloud architecture.
- Support AI-agentic workflows and knowledge graphs / semantic layers as part of the platform's data foundation.
- Automate build and deployment pipelines for the end-to-end customer lifecycle, and optimise components to run efficiently in the cloud.
- Proactively seek to link analytical outputs to commercial outcomes.
- Implement data quality checks, monitoring, and governance frameworks, and troubleshoot pipeline and infrastructure issues in a timely manner.
- Contribute to the product roadmap, sprint planning, and stand-ups, keeping the scrum board up to date.
- Document data engineering processes, workflows, and best practices to facilitate knowledge sharing and ensure reproducibility.
Our culture and values
Quantaco is a happy and diverse group of professionals who value a strong work ethic, authenticity, creativity, and flexibility. We work hard for each other and for our customers while having fun along the way. You can see what our team says about life at Quantaco here. If you've got a passion for creating new and impactful data-driven technology and want to realise your potential in a team that values your ideas, then we want to hear from you.
We'd love to hear from you if you
- Have 5+ years of experience in data engineering / analytics, ideally including senior or technical-lead responsibilities.
- Hold a Bachelor's or Master's degree in data science, mathematics, statistics, or computer science.
- Are strong in the core stack — production Python and SQL — with solid data design principles and hands-on experience developing and operating data pipelines.
- Are experienced with dbt-led ETL (and stored procedures), Jupyter Notebooks, and building maintainable, well-tested pipelines.
- Have worked across multi-cloud environments and their data services — ideally Google Cloud and Databricks.
- Have exposure to AI-agentic workflows and knowledge graphs / semantic layers, or a strong interest in building towards them.
- Are familiar with ML techniques, particularly around text analysis and classification.
- Can work with others to hypothesise and identify trends in data that achieve results for customers.
- Are organised, efficient, and a fast learner, with a scientific and design-led approach to delivering effective data solutions.
- Are self-motivated, work well independently and in a team, and are an excellent communicator — patient, and able to explain ideas clearly in speech and in writing.
It would be fantastic (but not essential) if you have experience with:
- Gemini Enterprise Agent Platform
- Multi-cloud architecture (GCP, Azure)
- AI-agentic workflows, orchestration, and knowledge graphs / semantic layers
- Python Django
- ML (text analysis, classification)
