Lead Data Engineer

Lead Data Engineer – London – £120,000
Sector:

AI Consulting | Client Delivery
Type:

Full-time | Hybrid

Join a tech consultancy at the forefront of applied AI—helping global brands design and deploy intelligent systems that solve real business problems. They combine deep engineering know-how with domain expertise to build the data infrastructure that powers machine learning and generative AI at scale.

About the Role
As a

Lead Data Engineer , you’ll play a critical role in delivering AI-driven solutions for clients—owning the architecture and development of robust, scalable data platforms that feed into machine learning models and intelligent applications.
You’ll work closely with Data Scientists, MLOps Engineers, and domain experts to ensure clean, accessible, and production-grade data pipelines are in place to support experimentation and deployment.

️ Key Responsibilities
Build and maintain high-performance data pipelines to power AI/ML use cases
Architect cloud-native data platforms using tools like

Databricks ,

Airflow ,

Snowflake , and

Spark
Collaborate with AI/ML teams to align data processing with model requirements
Develop ETL/ELT workflows to support feature engineering, model training, and inference
Optimise data workflows for scalability, reliability, and cost-efficiency
Ensure security, compliance, and data governance standards (e.g.

GDPR , RBAC)
Mentor junior engineers and guide technical decisions on client engagements

✅ Ideal Experience
Strong in

Python

and

SQL , plus familiarity with

Scala

or

Java
Experience supporting AI/ML workflows and working with Data Scientists
Exposure to cloud platforms:

AWS ,

Azure , or

GCP
Hands-on with modern data tooling:

Spark ,

Databricks ,

Snowflake ,

Airflow
Solid grasp of data modelling, orchestration, and infrastructure-as-code (Terraform, Docker, CI/CD)
Excellent communication and client-facing skills—comfortable leading on technical delivery

What’s on Offer
£120k base + bonus + flexible benefits
Career progression into technical leadership or architecture
Training, certifications, and access to internal AI communities
Flexible/hybrid working, wellness support, and inclusive culture
The chance to work on impactful AI projects across multiple industries