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About the Role

Data powers critical decisions at Stake, influencing customer behavior, product impact, and operational efficiency. As a Data Engineer, you will build scalable, high-quality data systems to empower teams across the business to make informed decisions.

Responsibilities

• Build and evolve reliable, scalable data pipelines.
• Increase trust in data by improving quality, observability, governance, and documentation.
• Enable teams to move faster through self-service data capabilities and well-designed datasets.
• Define and implement scalable data models.
• Improve the performance, efficiency, and maintainability of the data platform.
• Establish best practices for data engineering, modelling, testing, and platform reliability.
• Create robust datasets and metrics that inform strategic decision-making.
• Solve complex problems with clarity, pragmatism, and impact.

Requirements

• Strong experience building and maintaining modern data platforms, pipelines, and data products in production environments.
• Care deeply about data quality, reliability, and creating dependable systems.
• Comfortable working across the data stack, from ingestion and transformation through to modelling and consumption.
• Combine strong technical judgment with a practical mindset, balancing long-term platform health with business needs.
• Communicate clearly, simplify complexity, and enjoy partnering with technical and non-technical teams.
• Take ownership, move with urgency, and enjoy solving problems with meaningful customer and business impact.
• Experience with modern data technologies on Google Cloud Platform (GCP), including BigQuery, Cloud Storage, and Dataflow.
• Strong proficiency in SQL and data manipulation.
• Working knowledge of Python or another programming language.
• Experience with data warehousing and data modelling concepts.
• Understanding of data governance principles and best practices.
• Experience with reporting and visualisation tools, preferably Metabase.
• A desire to stay up to date with developments across GCP and emerging technologies, including AI.
• Working knowledge of Docker and Kubernetes is ideal, but not essential.
• Experience in fintech, financial services, or another highly regulated industry is a bonus.
• Experience building data platforms supporting product analytics, experimentation, or customer-facing products is a bonus.
• Experience with modern cloud data platforms such as BigQuery is a bonus.
• Experience contributing to data governance, lineage, or observability initiatives at scale is a bonus.
• Experience helping establish engineering standards, tooling, or platform capabilities for growing teams is a bonus.

Skills

• Google Cloud Platform (GCP)
• BigQuery
• Cloud Storage
• Dataflow
• SQL
• Data manipulation
• Python
• Data warehousing
• Data modelling
• Data governance
• Reporting tools
• Visualisation tools
• Metabase
• Docker
• Kubernetes

Location

• Sydney

Work Type

• Hybrid

Experience Level

• Mid-level

Benefits

• Professional development allowance
• Up to 16 weeks of paid parental leave
• Childcare allowance
• Wellbeing support
• Annual leave swap days
• Discretionary performance bonus
• Stake products discount
• 30% discount on an annual self-managed super fund (SMSF) membership
• A $295 annual trading credit
• A Stake Black account

About the Company

• Data powers some of the most important decisions at Stake. From understanding customer behaviour and measuring product impact to improving operational efficiency and uncovering new opportunities, our data platform helps teams move with confidence.
• Stake does not accept agency resumes. Please do not forward resumes to our jobs alias or directly to Stake employees. Stake is not responsible for any fees related to unsolicited resumes.