Lead Data Engineer

Lorien; Greater London; On-site; GBP 90,000 - 140,000; Full time

Job summary

Lorien in London seeks a Lead Data Engineer to tackle AI-driven data problems in a growing enterprise data capability. This is a hands-on technical leadership role with no line management.

You’ll design and implement robust, production-grade data pipelines across legacy systems and modern cloud environments, collaborating with stakeholders to turn messy realities into clear, usable data solutions.

Qualifications

• Senior/lead data engineering experience with AI exposure.
• Strong Python and Spark proficiency for production data pipelines.
• Experience designing data governance and data quality processes.

Responsibilities

• Design and build enterprise-scale data pipelines and services.
• Collaborate with stakeholders to turn messy realities into usable data solutions.
• Improve data integration, quality, and governance across environments.
• Resolve complex issues across legacy and modern cloud systems.

Skills

Senior / Lead Data Engineer

Python

Spark

Data pipelines

AI experience

Data modelling

Governance

Job description

Fix complex data problems that actually matter

We’re hiring a (AI) Lead Data Engineer to join a growing enterprise data capability in a hands‑on technical leadership role — no line management.

You’ll work across legacy systems and modern cloud, tackling real‑world complexity and delivering robust, production‑grade data solutions.

Why this role?

This is about doing, not directing.

You’ll lead through technical credibility, problem‑solving, and delivery — not hierarchy.

What you’ll do

• Design and build enterprise‑scale data pipelines and services
• Work with stakeholders to turn messy realities into usable data solutions
• Improve data integration, quality, and governance
• Solve complex issues across imperfect and legacy environments

What you’ll bring

• Strong experience as a Senior / Lead Data Engineer and previous AI experience
• Expertise in Python, Spark, and production data pipelines
• Deep understanding of data lifecycle & integration
• Experience with data modelling, governance, and quality
• A pragmatic, hands‑on mindset with strong ownership