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Data Tech Lead
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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.
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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
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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).
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