Senior Data Engineer Our financial services client is seeking a Senior Data Engineer to join a high-performing Data & Analytics team based in North Sydney. This role will play a key part in developing, maintaining and operationalising the Enterprise Data Warehouse, improving data frameworks, and building scalable pipelines that support analytics, reporting, data science and ML Ops initiatives. The role will work closely with technology, finance, treasury, risk, compliance and broader business stakeholders to improve access to trusted data and enable stronger self-service analytics capability across the organisation. Key Responsibilities Develop, maintain and operationalise the Enterprise Data Warehouse and Snowflake data hub. Build robust, scalable and testable data pipelines for batch and real-time data processing. Integrate third-party data sources using APIs. Use SQL and Python to combine, transform and prepare data for analytics and data science use cases. Support ML Ops and data science teams by preparing training and testing datasets, feature engineering, and contributing to modelling pipelines. Develop reusable datasets, self-service reporting assets and business intelligence solutions. Contribute to architecture and solution design, including documentation and presenting to architecture forums. Mentor team members and help establish best practice patterns across data engineering, feature stores and EDW development. Skills & Experience Strong SQL experience, particularly for database integration and data transformation. Hands-on experience with Python, ideally using libraries such as pandas, numpy, scikit-learn, SciPy, PyTorch or Matplotlib. Experience building and maintaining scalable data pipelines. Strong understanding of APIs, including development, integration and third-party data consumption. Experience with Snowflake, DBT, Azure Data Factory, API calls and stored procedures. Experience using Git or other version control systems. Exposure to ML Ops, feature engineering, modelling datasets or data science workflows. Experience with Azure, AWS Lambda/Azure Functions, Airflow, Data Vault modelling, Streamlit or DataRobot would be advantageous. Credit risk, financial services or business financial metrics experience would be highly regarded.
