Key Responsibilities

• 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.

What are we looking for

#### 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).

So, what’s in it for you?

• 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.