Original listing text, shown exactly as published by the company.
The Role
As Head of Data, you'll lead Lawhive's data function through a step-change in capability. Reporting directly to our CTO, Jaime, you'll own the data stack, build the data integration capability for acquired firms, and run a small high-quality team that partners with every function in the business.
This role is for someone who has done it before. You've migrated a scaleup's data stack end-to-end. You've integrated acquired-company data into a canonical model. You're AI-native in how you work and in what you build. And you're comfortable telling a CTO "this stack is wrong, and here's what we do instead."
What You'll Do
- Design and own the acquisition data integration playbook. Build a canonical Lawhive data model that future systems map to. Make firm onboarding a repeatable weeks-not-months process
- Partner with Strategy on metric definition. You own instrumentation, semantic layer, and accuracy. They own the metric tree. Together, you run the metric council
- Diagnose and improve our data stack in your first 12 months. Propose a target architecture against our goals of AI-native self-serve-first analytics (warehouse, modelling, semantic layer, BI, exploration). Replace tools where needed
- Make Lawhive self-serve on data. Build the platform, modelling, and semantic layer that lets business users explore, drill in, and answer their own questions
- Define and enforce data quality SLAs. Freshness, accuracy, ownership coverage, end-to-end lineage
- Lead and grow the data team. Coach analysts into stronger cross-functional partners. Hire and onboard a data integration engineer in year 1
- Drive AI-native practices inside the data function. Use LLMs for entity resolution, schema mapping, data quality, and exploration. Set the bar for how a data team works in 2026
- Be a key cross-functional partner to Product, Engineering, Finance, Strategy, and the operational teams within acquired firms
What you'll bringYou'll be a great fit for this role if
- You're commercially literate. You can partner with functional heads as a peer and translate business questions into data infrastructure
- You've owned a data stack end-to-end at a B2B SaaS scaleup. You can walk us through what you built, changed, why, and what you'd do differently
- You've built repeatable data integration patterns at an M&A-heavy company or rollup. Ideally, a B2B SaaS context. You know how to handle messy legacy systems and conflicting schemas
- You have strong opinions on the modern data stack and data modelling best practices: warehouse, modelling, semantic layer, BI tooling, exploration. You can defend trade-offs
- You're AI-native in your craft. You use Cursor, Claude, dbt AI, agentic notebooks daily. You've shipped AI features inside a data team (LLMs for entity resolution, schema mapping, data quality, exploration). You think LLMs change how data work gets done structurally, not just incrementally
Nice-to-haves
- Experience standing up a semantic layer (LookML, Cube, dbt semantic layer)
- Background at a PE-backed software rollup or M&A-heavy SaaS
- Familiarity with legal services, legal tech, or regulated marketplaces
Interview process
- Introductory call with our Talent team
- 1:1 with our CTO
- Practical and Technical assessment: stack diagnosis and migration approach on an anonymised Lawhive context
- Values interview with our Founders
- We offer!
