About the role
Are you a hands-on, experienced Senior Data Engineer looking for an exciting permanent opportunity to make a significant impact? Join our high-performing Data Platform team where your creativity and technical expertise will help shape the future of QIC’s data capabilities. You will play a pivotal role in maintaining and evolving our strategic technology platforms for Investment Teams, while fostering strong, collaborative relationships with key business stakeholders to deliver high-value outcomes. If you thrive in a dynamic, innovative environment and are passionate about delivering reliable, scalable data solutions—we’d love to hear from you.
Key responsibilities will include:
- Conducting detailed data analysis, documenting data objects, relationships, and system mappings.
- Assembling large, complex data sets to meet business requirements.
- Contributing to database design and development activities in close collaboration with the Global Real Estate Technology Squad.
- Develop and maintain robust, scalable ETL/ELT pipelines to support data ingestion, transformation, and integration across multiple systems and platforms.
- Collaborating with teams to deliver outcomes while adhering to QIC methodologies.
- Enhancing data system functionality by working with data and analytics experts.
- Contributing to the design and architecture of future data modernisation initiatives, with a focus on scalability, automation, and cloud-readiness.
About You
- Tertiary qualifications in Information Technology, Computer Science or similar.
- Strong attention to detail and demonstrated experience with SQL Server database implementation and programming.
- Proven experience across the full application development lifecycle: design, development, testing, implementation and handover.
- Demonstrated experience with data modelling and data warehouse architecture and implementation.
- Experience working with large data sets and developing data pipelines that move data from source systems to data warehouses, data lakes, and other data storage and processing systems.
- Experience with Azure Data Factory, Data Lake and Synapse Analytics.
- Proficiency in CI/CD pipelines, especially using Azure DevOps.
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