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Senior 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 a result of our incredible success and growth, we are looking for a Lead Analytics Engineer to join us.. Responsibilities include . Play a key role in the Analytics Engineering function and dbt environment. You will build and maintain scalable data models from the staging layer through to the "Golden Layer," with a focus on performance and reliability on AWS Redshift.. Serve as a technical data partner for Product, Operations, Commercial, and other business functions. You will translate business requirements into robust data models and ensure cross-functional teams have the reliable data foundations they need.. Work closely with the Lead Data Engineer and Analytics Lead to contribute to the overall data strategy. Support the growth of more junior team members through code reviews, knowledge sharing, and day-to-day guidance.. Contribute to the code-based backend of our BI environment (Lightdash & Count), supporting the development and maintenance of the Semantic Layer and assisting in the integration of AI capabilities (e.g text-to-SQL) to advance self-serve analytics.. Actively champion software engineering best practices within the data team, including Gitlab/GitHub workflows, CI/CD pipelines, testing frameworks, and documentation-as-code. Contribute to the development of automations and AI capabilities within the Analytics Engineering function.. A little bit about you.. We’d really like to hear from you, if you have. 3+ years of highly technical experience with dbt and SQL. You write DRY, optimised code, build macros, manage dbt packages, and can troubleshoot performance bottlenecks.. Strong hands-on experience with AWS Redshift (or a similar cloud warehouse like Snowflake/BigQuery), including solid understanding of query optimisation and warehouse architecture. You are familiar with DAG structures and how the transformation layer interfaces with orchestration tools like Apache Airflow or similar.. Some experience mentoring or supporting more junior data team members, whether through code reviews, pairing, or informal guidance. You enjoy sharing knowledge and contributing to a collaborative, inclusive engineering culture.. You're comfortable partnering with non-technical stakeholders across Product, Commercial, and Ops to understand data needs and translate them into well-structured solutions. You can proactively flag data quality or architectural issues and suggest improvements.. Solid experience working with the code-first backend of modern BI tools (ideally Lightdash & Count, or similar). You have a good understanding of Semantic Layer concepts and are keen to develop further in this area.. A genuine interest in engineering efficiency. You have some experience — or a strong appetite to build it — using AI and automation tools, scripting, and workflows to reduce repetitive manual work within a data function.. Company Location: United Kingdom.