Data and AI Engineer (Early Career)

Loveadmin; Brighton; On-site; GBP 35,000 - 50,000; Full time

Job summary

A data-driven company in Brighton is seeking an early-career Data & AI Engineer to enhance data quality and unlock AI-powered insights. You will collaborate with various teams, support data operations, and introduce automation to improve efficiency. Ideal candidates should possess solid qualifications in SQL and Python, experience in data validation, and AI familiarity. A commitment to learning and growth within the data space is essential for this hands-on, impactful role.

Qualifications

• 2+ years of experience with SQL in academic or commercial settings.
• 2+ years of Python experience, including application in real scenarios.
• Experience with cleaning, validating, and transforming data is necessary.

Responsibilities

• Maintain clean, structured operational data and support data enrichment.
• Build automations to reduce manual effort in various departments.
• Collaborate with non-technical teams to understand data needs.

Skills

Strong understanding of relational databases

SQL experience

Python experience

Data cleaning and validation

CRM data management

AI concepts familiarity

Analytical and problem-solving skills

Communication skills

Machine learning knowledge

Automation experience

Exposure to analytics/dashboarding

Job description

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
• 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:

• 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
• 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