Head of Data

Nothing
Onsite

About The Position

Nothing's data function is being built from scratch, and this is the role that starts it. You'll work directly with our leadership team across product, supply chain, commercial, and finance to map the company's most critical data problems and build the infrastructure that solves them. The goal isn't a perfect data warehouse. It's clean, normalised data that powers real decisions today and our AI ambitions tomorrow. You'll be the architect, the engineer, and the strategist, and you'll have the autonomy to do it your way.

Requirements

  • Deep hands-on engineering skill: you write code, you build pipes, you don't just direct others to do it
  • A track record in complex environments; hybrid hardware/software companies, scaling fintechs, or similarly messy multi-system organisations
  • Fluency in modern agentic and LLM workflows, and a clear understanding of what AI needs from a data layer to function reliably
  • Commercial instincts: you frame your work in terms of decisions enabled and revenue generated, not rows processed
  • Strong judgement about when to build robust, scalable architecture and when a scrappier pipeline is the right answer today
  • Experience connecting disparate systems - ERP, HRIS, mobile telemetry, operational trackers into clean, reliable outputs
  • Comfort operating as an individual contributor at senior level: you thrive without a team beneath you, and you enjoy getting into the weeds

Responsibilities

  • Map Nothing's highest-priority data use cases in your first 30–60 days, interviewing cross-functional leaders to surface where data can most directly move the needle
  • Design and build targeted pipelines that solve multiple business problems simultaneously connecting ERP, HRIS, Android/app telemetry, and bespoke trackers into a coherent data layer
  • Own the architecture end-to-end: you'll write the code, make the tooling calls, and be accountable for what gets built
  • Identify technical overlaps across use cases and group them into a pragmatic build sequence; no isolated hacks, no over-engineered warehouses
  • Ensure the data foundation is clean and normalised enough to eventually power an internal company brain and agentic workflows
  • Evaluate and select modern, lightweight tooling that accelerates our timeline rather than locking us into legacy platforms
  • Define what "good data" looks like at Nothing - standards, quality controls, and the documentation that makes it usable by others
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