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Analytics Engineer at Pion. A little bit about us…. Pion produces award-winning technology for the biggest retailers on the planet, connecting them with the youth market. We’re constantly innovating to offer new solutions that satisfy our consumers, drive ROI for our clients, and create an empowering workplace for our employees.. Life at Pion Where People Thrive. At Pion, we’re driven by big ideas and bold thinkers.. Our purpose is clear. We make it possible to reward those who shape our world, from Students to Healthcare workers and . more. . That mission demands diverse perspectives and a culture where everyone belongs.. Our people power everything we do from innovation to collaboration. We’re here to break down barriers and build a space where everyone can grow, learn, and thrive—because affordability starts with empowered people.. Check out our . SHARP values. to find out more about our culture.. Research. shows that while men apply to jobs when they meet 60% of the requirements, women and those in underrepresented groups tend to only apply when they tick every box. We don’t think you should have to tick every box. We value your uniqueness, and it goes without saying that all applications are welcome, even if you don’t think you fit the criteria. . Need any adjustments to support you with your application? Just drop us an email at . [email protected]. .. About the role.. As we continue to scale our data capabilities, we are looking for a Junior or Mid-level Analytics Engineer to join our growing Analytics Engineering team here at Pion. You will sit at the intersection of Data Engineering and Data Analytics, playing a pivotal role in democratising data access. Initially, you will focus on the "Exposure Layer" (Marts) and the models feeding into that—ensuring the data and metrics exposed to the business is pristine and reliable. You will be the key technical support for our BI environment (Lightdash), ensuring the connection between our data models and our end-users is seamless, while also leveraging new features in AI and the Semantic Layer.. This role is designed for growth. As you grow in the role and master our business logic, you will be exposed to increasingly technical challenges. You will have the opportunity to move upstream, taking ownership of comprehensive modelling techniques, architectural design, and complex transformations beyond the Marts and Transform layers.. Responsibilities include -. Maintain and optimise the Marts Layer, writing clean, modular SQL transformations in dbt that serve as the single source of truth for the organisation.. Act as the key technical support for the Business Intelligence environment (Lightdash). You will handle the configuration of the code-based modeling layer, troubleshoot technical issues, and ensure that metrics are defined consistently across the platform.. Drive adoption and trust by building "showcase" charts and visuals on top of your models. You will use these to demo new data capabilities to stakeholders, proving the reliability of the data and building their confidence to self-serve... Partner closely with the Data Analyst team to understand their requirements, handling the infrastructure work needed to expose the right data for their insights.. Help improve data literacy by supporting the rollout of AI capabilities within the BI tool (e.g., text-to-SQL assistants) and the dbt Semantic Layer.. Ensure data quality by adding tests to your models in dbt and responding to alerts to keep our pipelines healthy.. We’d really like to hear from you, if you have:. dbt & SQL Proficiency. - You have at least 1 year of hands-on experience with dbt. You write clean, readable production ready SQL and are comfortable with the basics of testing, and documentation-as-code.. BI Tool Development. - Experience developing in modern, code-first BI tools (for example Lightdash, Tableau or Looker). You aren't just modelling the data; you understand the underlying modeling languages (SQL, YAML or LookML) and how they connect to the warehouse.. Data Modeling Fundamentals . - You understand the concept of a "Golden Layer" and are eager to learn more advanced dimensional modeling concepts (star schema, fact/dimension tables, snapshots).. Data Stack Exposure. - You have exposure to (or a conceptual understanding of) cloud data warehousing for example: AWS Redshift and orchestration tools (like Airflow). You don't need to be an expert, but you understand where they fit in the modern data stack.. Collaborative Mindset. - You enjoy working in a team environment and partnering directly with Data Analysts and Business Stakeholders. You are eager to learn from senior analytics and data engineers.. Interest in Innovation & AI. - You are curious about the intersection of AI, Automation and Analytics. You want to learn how to implement AI-driven features and define metrics via the YAML Layer to help the business self-serve more autonomously.. Company Location: United Kingdom.