Analytics Engineer

Responsibilities

• Provide subject matter expertise to help shape and guide the overall data modelling strategy across our data domains.
• Design and implement dbt models on Databricks to support a comprehensive and unified view of subscriptions and content data.
• Build data products, not just reports – well‑modelled, reusable data sets that power dashboards, self‑serve querying and conversational analytics tools, with clear lineage back to source.
• Contribute to the ongoing evolution of our data platform by identifying and delivering improvements to data quality, coverage, and performance.
• Serve as a subject matter expert on data modelling, supporting analysts and stakeholders in understanding and using our data assets effectively.
• Design and implement scalable and maintainable dbt models on Databricks across our core data domains, including subscriptions and content.
• Create and maintain a suite of dbt tests to ensure data quality, consistency, and trustworthiness.
• Collaborate with data analysts, engineers, and business stakeholders to develop and maintain reporting marts that meet evolving analytical needs.
• Support the build‑out of self‑serve and conversational analytics capability, helping design data structures that natural language query tools can reliably and accurately query.
• Provide guidance on data modelling best practices, performance optimisation, and modular design in dbt.
• Participate in code reviews and knowledge‑sharing sessions to uplift team capability.

• Proven experience working as an Analytics Engineer, Data Engineer, or similar role.
• Deep proficiency in SQL for data transformation and analysis.
• Strong hands‑on experience with dbt (Data Build Tool) on Databricks, including advanced modelling techniques, test writing, and performance optimisation.
• Solid understanding of dimensional modelling and modern data stack principles.
• Familiarity with version control systems (e.g., Git) and collaborative workflows.
• Strong communication skills with the ability to communicate clearly and work independently with minimal supervision.
• A proactive, curious mindset: comfortable identifying problems and opportunities rather than only working from a ticket.
• Experience working with subscription‑based business models and datasets is highly desirable.
• Broader experience with cloud data platforms such as Azure, and familiarity with Databricks features beyond dbt, such as Delta Lake or Unity Catalogue.
• Familiarity with data visualisation tools and BI tools and their data requirements.
• Previous involvement in large‑scale data migration or re‑platforming projects.

Demonstrates expertise in data modelling and analytics engineering, with a strong focus on designing and implementing dbt models on Databricks. Proficient in SQL and experienced in building scalable data products that enhance data quality and support analytical needs.

• Databricks
• Azure
• Delta Lake
• Unity Catalogue
• Version Control Systems
• Data Visualisation Tools
• BI Tools