Head of Data (London)

Conveo; Greater London; Presencial; GBP 120.000 - 180.000; Tempo integral

Resumo da vaga

Conveo is seeking a Head of Data to own the data stack from the warehouse to the dashboard. You will build and scale the data team across London or Antwerp, shaping how data informs marketing, product and research decisions.

You will own BigQuery, transformation layers, and BI tooling, while ensuring data reliability, consistent metrics, and a clear data strategy for AI-ready insights across the business.

Qualificações

• Experience leading data at a startup or scale-up.
• Hands-on BI and analytics experience across data sources.
• Ability to translate business needs into data solutions.
• Proven track record building data platforms and teams.

Responsabilidades

• Own the data stack end to end from warehouse to dashboards.
• Define data access rights and build a single source of truth.
• Own metric definitions and enable analytics across teams.
• Lay groundwork for future ML and data science initiatives.

Conhecimentos

Data leadership

BI & analytics

Cross-functional partner

Ferramentas

BigQuery

dbt

Cube

Metabase

Descrição da vaga

The Role

We'll own Conveo's data, from the warehouse to the dashboard, and build the team every part of the business relies on. This role can be based from either our London or Antwerp location. Conveo is building the AI-powered infrastructure for consumer understanding, making consumer and B2B research fast, affordable and high quality. Global brands such as Unilever, Google and Orange use our AI video interviewer to generate insights across their marketing, product and research teams. Backed by Y Combinator, we are in a period of rapid growth. We started this year with around 20 people and are on track to reach around 120 by year end, so the people who join now have an outsized chance to shape how the company is built. We raised a $50M Series A led by DST Global, giving us the fuel to move even faster. We are investing in our product, growing an exceptional team, and taking on bigger challenges as we enter our next stage of growth.

What You'll Do

• Own the data stack end to end
• Take ownership of our warehouse (Google BigQuery), our transformation and semantic layers (dbt and Cube today) and our BI tooling (Metabase today)
• Review what's been built with a critical eye, and get it ready to scale as new tools and data sources come in
• Think through access rights, so it's clear who can see customer, HR and financial data once it all lives in one place
• Build one source of truth the business trusts
• Own metric definitions, so every team works from the same numbers
• Close the gaps that matter most, starting with areas like marketing attribution and the data our finance team needs for its analysis
• Make our data reliable enough that people trust it and act on it
• Turn data into insight for every team
• Act as the translator between engineering and the business: ask engineers the hard questions about what to build, and explain data in plain English to everyone else
• Swap today's sprawl of one-off dashboards and AI-generated reports for a clear set of things people actually need to look at
• Use AI well, without the slop
• Shape our data so AI tools can use it reliably
• Help the business get real value from AI for analysis, without a flood of low-quality output
• Build the data team
• Hire your first team members, and set out what the BI team should look like as we grow
• Lay the groundwork for machine learning and data science later on

What Success Looks Like

• After one month: you know our data infrastructure properly and have run a full gap analysis covering what we take in, what we understand and what's missing. You also have a plan for what to fix first and a plan for the team, including your first hires.
• After three months: you've reviewed the setup in place and own BigQuery, the transformation layer and our BI tooling, and our systems are ready to scale. Teams are already using data better because of work you've delivered.
• After six months: every department is running with deep insights and analytics, and our leaders have the confidence and ability to use the data themselves.
• Throughout: people trust the numbers, the business has the dashboards it needs rather than a thousand it doesn't, and we know who the data team hires next.

What You'll Bring

• Experience leading data at a startup or scale-up, as a Head of Data, Head of Analytics or similar. Ideally you've been at a Series B company or later and have seen what good structure looks like at the next stage.
• Hands-on BI and analytics experience. You've done the insights work, not only data engineering, and you know what good BI looks like.
• Enough technical depth to ask engineers the hard questions, and a clear understanding of how data flows from the warehouse through transformation and semantic layers into a BI tool.
• A problem solver's instinct: you can talk to a depa