Staff Engineer, Data & AI Platform (Remote)

Arbor Education; United Kingdom; Remote; GBP 120,000 - 160,000; Full time

Benefits offered by this job

Wellbeing team initiatives

32 days holiday + bank holidays

Life Assurance 3x salary

Job summary

Arbor Education is seeking a Staff Engineer to set architectural direction across data domains, including OLTP, OLAP, and AI foundations. You will partner with Technical Leads and Product Directors to shape the data platform and drive AI-enabled product capabilities.

This role requires hands-off leadership with deep technical expertise and a track record of delivering scalable data systems. You will influence multiple teams, own architectural reviews, and help transform Arbor’s data strategy to

Qualifications

• Extensive experience overseeing data architecture across multiple OLAP domains.
• Strong grounding in data modelling techniques (Star, Medallion) and cloud-native data environments.

Responsibilities

• Define and evangelise target architectures bridging transactional, analytical, and AI systems.
• Lead end-to-end data lifecycle governance including OLTP/OLAP.
• Mentor Technical Leads and collaborate with Product Directors to align technical and business goals.
• Drive AI-first data foundations and architecture for AI product enablement.
• Architect future infra for LLM orchestration, RAG and real-time inference at scale.

Skills

Data architecture

Data modelling (Star, Medallion)

Cloud-native data systems

AI/ML Engineering & MLOps

DataOps & CI/CD for data

Stakeholder influence & leadership

Tools

Snowflake

Job description

Arbor Education is seeking a Staff Engineer to set architectural direction across data domains, including OLTP, OLAP, and AI foundations. You will partner with Technical Leads and Product Directors to shape the data platform and drive AI-enabled product capabilities.

This role requires hands-off leadership with deep technical expertise and a track record of delivering scalable data systems. You will influence multiple teams, own architectural reviews, and help transform Arbor’s data strategy to