Senior Data Engineer

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.