Analytics Engineer

• •Ownership of the Modern Data Stack (dbt & BigQuery)
• •Act as a lead developer for our dbt project.
• •Build performant, modular, and well-tested models that turn data into a reliable "Source of Truth."
• •Apply software engineering rigor to the data stack: version control (Git), documentation, unit testing, and CI/CD.
• •Partner with business leads across the company to identify manual processes that can be streamlined through data automation.
• •Bridge the gap between the warehouse and the business by "closing the loop"—ensuring data isn't just sitting in a dashboard but is actively driving operational tools and decision-making.
• •Leverage AI tools and LLMs to accelerate development cycles, automate documentation, and explore new ways to enhance data quality.
• •Act as a consultant to business leads. Don't just "take tickets"—understand the underlying business logic and propose better ways to structure data.
• •Translate loosely defined business requirements into robust, automated technical solutions.
• •Work closely with stakeholders to define data quality standards and establish feedback loops that ensure data captured in upstream systems is accurate, complete, and fit for purpose.

• •30 days annual leave each year, excluding bank holidays.
• •4 wellbeing days per year to prioritise your mental health.
• •1 company volunteering day per year.
• •Strong benefits package including; Private Healthcare, Pension, Income Protection (long-term absence), Life Insurance, Menopause Policy, and an enhanced Parental Leave policy.
• •Opportunities for personal growth and professional development.
• •Collaborate with teams on a hybrid working arrangement.
• •Empowering culture focused on personal growth and team success.

#### Essential Skills and Experience

• •3+ years of experience in a high-growth data environment (Analytics Engineer, Data Engineer, or Technical Data Analyst).
• •Deep, practical knowledge of dbt and cloud warehouses (we use BigQuery, but the experience is very transferrable).
• •Expert-level SQL: You write complex, clean, and performant queries.
• •Python Literacy: Not a software developer, but you must be comfortable reading code, writing scripts for data manipulation, and handling API.
• •AI Comfort: You are an "AI-first" builder who is comfortable using AI tools (e.g., Cursor, GitHub Copilot, LLMs) to write code faster, debug, and stay ahead of the curve.
• •Ownership Mindset: You are comfortable working independently, managing your own roadmap, and taking accountability for the entire warehouse architecture.
• •Exceptional Communication: You can walk into a room with a non-technical team, understand their pain points, and explain your technical solution in plain English.

#### Desired Skills and Experience

• •Experience with tools like n8n, Zapier, or similar automation platforms.
• •Experience with Looker, Thoughtspot, or similar BI/Semantic platforms.
• •Experience in Payments, FinTech, Banking, or Cryptocurrency.
• •Familiarity with moving data from the warehouse back into SaaS tools (Reverse ETL).