Job Opportunities API

Purpose of the Position Data is at the core of the company’s decision‑making and commercial success. Our mission is to ensure that Awin leverages the full value of its data assets to drive strategic insight, optimise campaign performance, and empower client‑facing teams with best‑in‑class intelligence. We are looking for an experienced Analytical Engineer to join our BI team and shape the data foundation that powers self-serve analytics across the business. This is an exciting opportunity to establish our Analytical Engineering practice from scratch, working on a modern Databricks stack with Tableau and Power BI as our primary BI tools. This role sits at the intersection of Data Engineering and BI. You will work closely Data Engineering who own our data pipelines, Databricks infrastructure and data intelligence, and with BI Developers and Insight Analysts who deliver reporting and insight to stakeholders. The purpose of this role is to bridge both worlds, taking reliable data from our reporting layer and transforming it into a trusted, well-documented semantic layer that the whole team can build from. The ultimate goal is to successfully unlock self serve reporting across the organisation. Key Tasks & Accountabilities Build the Analytics Engineering practice Provide the business context for the mart layers of our data architecture, feeding into BI-ready tables that support self-serve analytics across the business. Create a single source of truth for business metric definitions - KPIs, business logic, and calculation rules. This should be accessible to all BI tools. Take responsibility for data quality initiatives and own documentation around the semantic layer. Work across teams Partner with Data Engineering to agree handoff boundaries, raise upstream data requirements, and flag quality issues at source. Work with Insight Analysts to encode business logic and stakeholder requirements into reliable, reusable data models. Support BI Developers in consuming the semantic layer efficiently within Tableau and Power BI. Participate in regular cross-departmental syncs with Data Engineering to keep both teams aligned. Upskill and develop the team Work closely with the BI Manager to coach BI Developers in Analytics Engineering best practices considering tools such as dbt Create clear documentation and playbooks so that team members can contribute to any dbt project independently. Be an internal advocate for Analytics Engineering standards across both the BI team and Data Engineering. Drive self-serve analytics Design data marts with self-serve usage in mind. Clear naming, consistent grain, reliable refresh cadence. Work with Insight Analysts to identify which stakeholder questions can be answered via self-serve and model accordingly. Reduce ad-hoc data requests by making well-structured, trustworthy data accessible to the business. Ensure the semantic layer is AI-ready. Clean, governed, and documented so that AI and GenAI tools can operate on our data without ambiguity.   Skills & Expertise Strong, hands-on SQL. Comfortable writing complex transformations, optimising queries, and reviewing others’ code. Proven experience with dbt (Core or Cloud) in a production environment. Experience working with a cloud data warehouse or lakehouse. Databricks preferred, but others also relevant (Snowflake, BigQuery etc) Solid understanding of data modelling concepts: dimensional modelling, star schemas, and slowly changing dimensions. Comfortable working in a code-reviewed, version-controlled workflow. Experience working alongside or within a BI team. Understanding what BI Developers and Insight Analysts need from the data layer. Ability to translate ambiguous business requirements into clear, well-documented data definitions. Strong communication skills. Able to explain technical concepts to non-technical stakeholders and align ac