Data and AI Engineer (Early Career)
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