Data Tech Lead

Data Tech Lead

Tech: Python, SQL, Snowflake

Office : Remote, but meet up once a month or so in London

Salary : £90,000 to £110,000 + Bonus

Eng Size : 50

We're working with a globally recognised tech-for-good platform helping organisations build more sustainable, responsible supply chains. Backed by a huge global customer base and years of rich data, they're investing heavily in AI to shape their next-gen product.

They need a hands-on Data Tech Lead to own engineering for a small cross-functional data pod — building and evolving the pipelines, models and services that turn supply chain data into customer-facing insight. You'll combine hands-on data engineering, technical leadership and line management, and be the technical role model for your pod.

What you'll do:

• Design and build ingestion, ETL/ELT and data-serving pipelines in Python and SQL, including relational, non-relational and Snowflake warehouse models
• Own data quality end-to-end — data contracts with suppliers/consumers, automated data + code testing, lineage, cataloguing, and governance
• Line-manage your engineers — 1:1s, growth, accountability, culture
• Drive AI-assisted development — daily use across pipeline code, SQL and data quality checks; coach the team; evaluate tooling; set standards for reviewing AI-generated code and data transformations
• Remove bottlenecks, simplify data models/architecture, improve CI/CD and local data environments

What they need:

• 3–5 years senior-level experience in data teams
• Strong production experience with data pipelines/services in Python and SQL
• Ability to design relational, non-relational and Snowflake warehouse data models; solid grasp of ingestion, ETL/ELT, quality, governance and DataOps
• Experience co-creating data contracts and driving automated testing (TDD + data quality)
• Experience defining non-functional requirements (performance, maintainability, cost) and operating data systems in production cloud environments
• 1+ year using AI coding assistants, can speak to benefits/limits
• Experience mentoring or line-managing engineers

Bonus: real-time/message-based architectures (e.g. Kafka), ML/AI data pipeline expertise, or a software engineering background with cloud-native tooling (Docker, Kubernetes, Terraform).