Location: Brighton Marina, UK (Hybrid)
Reporting to: Lead Data Engineer
The Role:
We are looking for an early-career Data & AI Engineer to join our data function and work closely with an experienced Lead Data Engineer. This role is suited to someone with a strong academic foundation in computer science, data, or AI, and some commercial experience applying those skills in real-world environments.
You’ll have responsibility for improving the quality, accuracy and usability of our customer and platform data, while unlocking automation, reporting and AI-powered insights across the business. You will directly contribute to a variety of automation initiatives, helping to apply AI techniques to operational problems across the business, enriching and segmenting CRM prospect data for revenue growth and influencing cross-team workflows and processes.
This is a hands-on technical role with strong exposure to business operations, working alongside marketing, sales, onboarding, customer success, and product teams to help them operate more efficiently and make better data-led decisions.
Key Responsibilities:
1. Data operations & support
* Maintain clean, accurate, and well-structured operational data
* Support and implement data enrichment and segmentation strategies
* Support data cleaning, validation and transformation
* Assist with data migration and operational data support
2. Automation & process improvement
* Contribute to building and maintaining automations that reduce manual effort across onboarding, customer success, marketing, and sales
* Support the extraction, transformation, and validation of operational datasets
* Help translate repetitive or inefficient processes into systemised or automated solutions
3. Applied AI & optimisation
* Work with the data team to identify where AI techniques can support internal workflows and decision-making
* Assist in prototyping and testing AI-enabled use cases such as workflow automation, scoring, classification, or internal tooling
* Apply academic or early commercial AI knowledge to practical business problems
4. Cross-functional collaboration
* Proactively source and shape data to surface trends and identify market opportunities for prospecting customers
* Support the rollout and adoption of new data tools, automations, or processes
* Work day-to-day with non-technical teams to understand data needs and operational challenges
* Help explain outputs and findings clearly to non-technical stakeholders
5. Analytics & reporting
* Support the creation and maintenance of reports or metrics used by operational teams
* Assist with monitoring data quality and system health
* Contribute to analysis that helps teams understand onboarding progress, usage patterns, or operational performance
Requirements:
Essential
* Strong understanding of relational databases
* SQL experience (approx. 2 years, inc. academic or commercial use)
* Python experience (approx. 2 years, inc. academic or commercial use)
* Experience cleaning, validating and transforming data
* CRM data management or operational data mapping experience
* Familiarity with AI concepts and their practical application
* Strong analytical and problem-solving skills
* Ability to communicate clearly with both technical and non-technical colleagues
Desirable
* Familiarity and applied knowledge of machine learning
* Experience with automation or process improvement
* Exposure to analytics or dashboards
Personal Attributes
* Curious and eager to learn
* Pragmatic and focused on delivering practical outcomes
* Able to balance technical quality with business needs
* Motivated to grow into a more senior data or AI role over time
What Success Looks Like
* Operational teams trust the data they use day to day
* Manual data work is reduced through automation and better processes
* Migrations and operational support tasks are delivered accurately and on time
* AI and optimisation techniques are applied pragmatically to real business problems
* You grow in confidence, technical depth, and independence over time