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About the Role
The AI & Data division is transforming CFS through end-to-end delivery of data programs and projects. This role is part of the Group Data & Analytics domain, focusing on the Data Engineering space to drive insight and decision-making capabilities across the organisation.
Responsibilities
- Provide technical solutions to enhance data engineering capabilities, ensuring high availability, performance, and security of data environments.
- Resolve challenges using domain knowledge and contribute to engineering outputs to a production level quality through code artifacts.
- Combine operational mindset with a focus on data engineering solutions.
- Collaborate with project teams to review and guide code changes, ensuring alignment with best practices and architectural standards.
- Produce engineering outcomes that meet the team's Ways of Working, including documentation, unit testing coverage, code quality scores, and acceptance targets.
- Align to technology frameworks and processes agreed by the team.
- Collaborate with stakeholders to understand data requirements and ensure the data warehouse meets their needs.
Requirements
- Proven experience as a data engineer with relevant experience in designing, building, and managing scalable, secure, and high-performance data products.
- Understanding of cloud-based data engineering principles, data governance, and modern data platform architectures.
- Experience with Azure Databricks, Databricks Unity Catalog, Databricks AI suite, Azure Data Factory, ADLS, and Azure Functions.
- Proven ability to develop and manage CI/CD pipelines (Azure DevOps/GitHub) and Terraform for application deployments.
- Skilled in Python, PySpark, DataFrames, and SQL for data engineering, including reusable libraries and scalable ingestion patterns.
- Familiarity with data orchestration and large-scale ingestion patterns.
- Experience in Data Model implementation.
- Knowledge of data governance, metadata management, data lineage, and information security controls.
- Knowledge of medallion architecture in Databricks.
- Familiarity with Databricks AI features such as AI workload optimisation and model inference.
- Experience in the Financial services sector.
- Full work rights in Australia.
Skills
- Data Engineering
- Cloud-based data engineering
- Data governance
- Modern data platform architectures
- Azure Databricks
- Databricks Unity Catalog
- Databricks AI suite
- Azure Data Factory
- ADLS
- Azure Functions
- CI/CD pipelines
- Azure DevOps
- GitHub
- Terraform
- Python
- PySpark
- DataFrames
- SQL
- Data orchestration
- Large-scale ingestion patterns
- Data Model implementation
- Metadata management
- Data lineage
- Information security controls
- Medallion architecture
- Databricks AI features
- AI workload optimisation
- Model inference
Location
- Sydney
Work Type
- Hybrid working model
Experience Level
- Proven experience as a data engineer
Benefits
- Additional day for your birthday
- Hybrid working model
- Access to CFS Employer Super
- Life Leave - 3 days per annum
- Access to Sonder for medical, mental health, and safety support
- Access to Corporate rates with BUPA Health Insurance
- Confidential coaching and counselling services
About the Company
- CFS values expertise, passion, and diversity.
- The company believes its success lies in its exceptional people, celebrating individuality, having a passion for high performance, and creating an environment where employees can unleash their full potential.
- CFS is committed to creating a thriving environment where individuals can flourish, built upon strong teams, celebrating uniqueness, championing individuality, and supporting a diverse and inclusive workforce.
- CFS aims to help Australians achieve their financial freedom.
Equal Opportunity
- CFS is committed to supporting a diverse and inclusive workforce.