About the job

Tech Lead – Data Engineering

📍 London | Hybrid – 2–3 days per week

💰 Up to £125,000 + benefits

A high-growth technology business is looking for a hands-on Tech Lead – Data Engineering to take ownership of its data platform and play a key role in shaping its wider data and AI strategy.

This is a senior technical leadership position for someone who enjoys operating at the intersection of data engineering, software architecture and technical strategy — without becoming detached from the code.

The opportunity

You’ll take end-to-end ownership of the data ecosystem, defining how data is ingested, stored, transformed and exposed across the wider platform.

The business is investing heavily in its data and AI capabilities, so this person will have significant influence over how the underlying data foundations evolve and support future ML-powered products.

You’ll be expected to make architectural decisions, establish engineering standards and provide technical leadership, while still spending a meaningful amount of time building and improving production systems.

What you'll be doing

• Own the technical direction and architecture of the data platform
• Design and build scalable, reliable data pipelines and distributed systems
• Define data models, schemas and data contracts
• Work closely with engineering and product teams to enable ML/AI-powered products
• Set engineering standards around testing, CI/CD, version control and maintainability
• Make pragmatic decisions around performance, cost, latency and data quality
• Remain hands-on with Python, SQL and production data systems
• Lead technical discussions, architecture reviews and code reviews
• Mentor engineers and raise engineering standards across the data domain
• Take ownership of production reliability, observability and data quality
• Improve operational workflows through automation

What we're looking for

You'll likely have experience as a Tech Lead, Principal Engineer, Staff Engineer or similar, with a strong background in data engineering and distributed systems.

We're particularly interested in people who have:

• Strong Python and software engineering fundamentals
• Advanced SQL and experience with modern cloud data platforms
• Experience designing and operating production-grade ETL/ELT pipelines
• Experience with tools such as dbt, Airflow or equivalent
• Strong architectural and system-design experience
• Experience working with ML systems or production AI/ML infrastructure
• A strong understanding of engineering practices across CI/CD, testing and Git
• The ability to balance technical quality with commercial and operational realities
• Experience providing technical leadership and mentoring others

Experience with Snowflake, Pandas/Polars, Looker/LookML, workflow automation or multimodal data would be beneficial.

The type of person they're looking for

This isn't a role for someone who wants to sit purely in architecture meetings — equally, it's not simply a senior individual contributor position with a different title.

The ideal candidate is hands-on, commercially aware and capable of thinking several steps ahead. Someone who has seen a smaller or scaling organisation evolve, understands the realities of building systems with limited resources, and can combine strong technical judgement with genuine leadership.