Lead Analytics Engineer

Overview

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

As a result of our incredible success and growth, we are looking for a Lead Analytics Engineer to join us.

• Analytics Engineering Ownership:
  Take full ownership of the Analytics Engineering function and the dbt environment. You will design scalable data models from the staging layer all the way up to the "Golden Layer," ensuring performance and reliability on AWS Redshift.
• Internal Data Consulting:
  Act as a strategic technical consultant for Product, Operations, Commercial, and other business functions. You will provide expert data support, translate complex business requirements into robust data models, and ensure cross-functional teams have the reliable data foundations they need.
• Cross-Functional Leadership & Management:
  Work hand-in-hand with the Lead Data Engineer (upstream infrastructure) and the Analytics Lead (downstream insights) to shape the overall data strategy, reporting directly to the Head of Data. Line manage, mentor, and upskill an initial team of two Analytics Engineers. You will conduct 1:1s, guide their career progression, establish engineering standards, and oversee code reviews.
• BI Infrastructure & Semantic Layer:
  Own the code-based backend of our BI environment (Lightdash & Count). While the Analytics Lead drives the overarching BI strategy, you will be responsible for the underlying infrastructure, architecting our Semantic Layer, and pioneering the integration of AI capabilities (e.g., text-to-SQL) to maximise self-serve analytics.
• Engineering Best Practices & Automation:
  Champion software engineering best practices within the data team, including Gitlab/Git Hub workflows, CI/CD pipelines, robust testing frameworks, and comprehensive documentation-as-code. Own the development of automations and AI capabilities within the Analytics Engineering function.

• Advanced dbt & SQL Mastery: 4+ years of highly technical experience with dbt and SQL. You write DRY, optimized code, build macros, manage dbt packages, and can troubleshoot performance bottlenecks.
• Cloud Data Warehousing & Orchestration:
  Deep, hands-on experience with AWS Redshift (or a similar cloud warehouse like Snowflake/Big Query), including a strong understanding of query optimization and warehouse architecture. You understand DAG structures and how to interface your transformation layer with DE's orchestration tools like Apache Airflow or similar.
• Leadership & Management
  
  Experience:
  
  Experience mentoring or line managing more junior data team members. You know how to elevate a team's technical baseline, conduct meaningful 1:1s, and foster a collaborative, psychologically safe engineering culture.
• Consultative Approach & Strategic Thinking:
  You excel at partnering with non-technical stakeholders across Product, Commercial, and Ops to solve complex data challenges. You proactively identify…