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Lead Data​/Head of Data Engineer

Job in Reading, Berkshire, RG1, England, UK
Listing for: Tank Recruitment
Full Time position
Listed on 2026-02-27
Job specializations:
  • IT/Tech
    AI Engineer, Data Engineer, Data Science Manager, Machine Learning/ ML Engineer
Job Description & How to Apply Below
Lead Data Engineer/Head of Data

Permanent

On behalf of a fantstic cleint we are resourcing for the following role

This is a senior, hands-on technical leadership role reporting directly to the CTO. You'll shape and deliver a modern data and AI platform, lead a small team of data and analytics engineers, and embed machine learning, AI agents, and advanced analytics into real customer workflows.

The Role

You'll own the end-to-end data and AI capability - from platform architecture through to production ML systems - ensuring data and AI are applied thoughtfully, responsibly, and with clear business impact.

What You'll Do

Design and evolve a secure, scalable data & AI platform with Snowflake at its core

Build production-grade data pipelines, models, and data products for analytics and AI use cases

Design, train, and deploy ML models, embeddings, and vector stores to enable AI-driven experiences

Lead and mentor a small, high-impact team of data and analytics engineers

Partner closely with Product, Engineering, and Infrastructure teams

Set standards for data quality, governance, security, and performance

Act as a trusted technical advisor to the CTO and senior leadership

What We're Looking For

Essential

Expert-level Snowflake experience (modelling, optimisation, advanced features)

Strong Python skills across data engineering, ML, and AI development

Proven experience delivering production ML systems

Hands-on experience with embeddings, vector databases, and LLM-driven systems

Deep understanding of modern data engineering practices (ELT, orchestration, versioning)

Nice to Have

Background in data science or applied ML

Experience building AI agents or intelligent automation

Familiarity with cloud-native architectures and MLOps
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