Associate Director, Data Engineer

Grade Level (for internal use): 12 The   Role:   Associate Director, Data Engineer   The Team:    The Digital Technology Services (DTS) Business Intelligence team is responsible for providing DTS and the wider organization with data and insights through reporting on and around IT, Financials, and other corporate datasets. We are seeking an experienced and forward-thinking Senior Data Engineer to join the team. In this role, you will design and build the pipelines, lakehouse datasets, and Power BI data products that our internal customers rely on — from senior leadership to individual users — and set the engineering standards the team builds to . You will work across the full data-to-insight lifecycle, from extraction and data wrangling through to modelling, reporting, and ongoing support, using Databricks, Microsoft Fabric, Azure, and Power BI.   The Impact:  The Senior Data Engineer will be instrumental in how our organization understands and uses its corporate and technology data. By building reliable, well-modelled, and well-documented datasets and the reporting layer on top of them, this role will directly improve operational decision-making and reduce the time it takes to get from question to answer. The work will have downstream impact on our customers by ensuring our organization operates on reliable, high-integrity data — enabling faster insight, better governance, and a stronger data foundation across the enterprise.   What’s in it for you:    Strong learning and growth opportunities: This role offers strong learning opportunities through close collaboration with experienced data professionals, along with hands-on exposure to building enterprise data products end to end.    Own high-impact, enterprise-wide data products: Take ownership of datasets and reports that underpin decision-making across DTS and the wider organization — a role with visibility across technology leadership and business stakeholders.   Work across the whole data lifecycle: Exciting and varied data, with each set presenting new and interesting challenges across extraction scripts, data wrangling and engineering, modelling, and reporting.   Breadth of modern tooling: Gain hands-on experience with Databricks, Microsoft Fabric, Azure, and Power BI in a live enterprise environment, and help shape how the team uses them.

Design, build, and maintain scalable ETL/ELT pipelines that ingest data from diverse source systems into our lakehouse and warehouse.   Apply data manipulations and transformations in SQL, Python, and Power BI (DAX / Power Query), and maintain and update the datasets our data products depend on.   Design and evolve data models and gold-tier datasets in Databricks and Microsoft Fabric for downstream reporting, consumption, and distribution.   Leverage Azure cloud services for scalable data ingestion, transformation, storage, and processing.   Implement automated job scheduling, monitoring, and observability, with self-healing capabilities where possible.   Own data quality in reporting and crafted data through automated testing, validation, reconciliation, and continuous improvement.   Document data manipulations and transformations for the data dictionary, and uphold coding standards, code quality tooling, and automated test coverage across the team's codebase.   Work with the data produced at the data engineering layer to build useful, performant visualizations in Power BI. Build and maintain Power BI dataflows and semantic models, and set reports up to refresh reliably on an ongoing basis.   Work with stakeholders to refine reports, and document each report and its inner workings so the team can assist in maintenance and improvements.   Drive strategic initiatives that enable the team to deliver better products, faster and with world-class support; champion support best practices and improve our users' experience.   Work closely with the scrum team, product