Data & AI Engineer

Overview

As a Data & AI Engineer, you will design, build and support scalable data and AI solutions to enable analytics, automation, and business outcomes. You will optimise Snowflake-based data platforms to support reporting, data science and ML workloads. You’ll craft reliable data pipelines aligned with governance and security standards. You’ll work with cross-functional teams to promote best practices in SQL, Python, data modelling and AI development. You will drive adoption of AI, ML and generative AI to deliver innovative business solutions, while improving platform performance and governance.

Pay / Benefits

• Attractive salary based on experience + car allowance
• Flexible working – hybrid
• Competitive annual bonus
• Private medical insurance (PMI)
• Pension with employer contributions
• 27 days annual leave + bank holidays

Responsibilities

• Design, build and support scalable data and AI solutions
• Optimize Snowflake-based data platforms for reporting, data science and ML workloads
• Create automated, observable data pipelines with governance and security
• Collaborate with stakeholders to promote best practices in SQL, Python, data modelling and AI development
• Advance adoption of AI, ML and generative AI to deliver business solutions
• Improve platform performance, scalability and operational efficiency with MLOps practices

Key requirements

• Experience with Snowflake including SQL development, data modelling and orchestration
• Azure services familiarity (Data Factory, DevOps, Functions, Logic Apps)
• Proficiency in Python for data processing and automation
• Understanding of cloud-native data platforms and modern data architectures
• Exposure to AI/ML or generative AI in business settings
• Experience with Agile delivery (Scrum/Kanban)
• Experience with modern data engineering tools (Airflow, dbt, Dataform)
• Strong analytical and stakeholder management skills

• Strong communication, able to explain technical concepts to non-technical audiences
• Collaborative mindset with cross-functional teams
• Problem-solving and analytical thinking
• Snowflake SQL development
• Data modelling and orchestration
• Azure Data Factory, Azure DevOps, Azure Functions, Logic Apps

…