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Data","description":"<p><strong>Why this role exists:</strong></p><p>The Engineer (Data) develops and maintains the robust data pipelines and transformations required to power Officeworks’ enterprise data platform and emerging AI capabilities. The role supports the Technology function by integrating diverse data sources into Snowflake, ensuring high data quality and system reliability to enable a self-serve analytics model. It plays an important part in the execution of the enterprise data strategy, helping Officeworks to democratise data access and drive informed decision-making across the business.</p><p><strong>Where you will make a difference:</strong></p><p><strong>In this role you will:</strong></p><p><strong>Data Engineering &amp; Pipeline Development</strong></p><ul><li>Develop, maintain, and optimise scalable data pipelines to support business-critical reporting and analytics.</li><li>Integrate complex data sets from various sources, including SAP Datasphere, Salesforce, and Adobe, into Snowflake.</li><li>Support the implementation of data modelling and transformation logic to ensure data is fit for purpose.</li></ul><p>&nbsp;<strong>Operational Monitoring &amp; Reliability</strong></p><ul><li>Monitor pipeline health and proactively address failures to maintain data integrity and availability.</li><li>Troubleshoot and resolve data-related issues, ensuring minimal disruption to downstream 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AI Team: Partner with the Data Platform Manager, Technical Associate Managers, and peer Engineers to deliver integrated data solutions.</li><li>Analytics Teams: Collaborate with Data Scientists and Analysts to provide the foundational data structures required for machine learning and AI initiatives.</li><li>Architectural Leads: Work with the Data Architect to ensure pipelines align with the enterprise data strategy and Snowflake platform standards.</li><li>Functional Business Partners: Engage with stakeholders across Salesforce, Adobe, and SAP workstreams to understand source system complexities.</li></ul><p><strong>What success looks like:</strong></p><ul><li>Pipeline Reliability: Data pipelines are highly available, with minimal downtime and rapid resolution of identified failures.</li><li>Data Democratisation: Successful integration of key data sources into Snowflake, enabling self-serve capabilities for business users.</li><li>Continuous Improvement: Demonstrable improvements in 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