Job Description
💼 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