Head of Data
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Key skills for this role
About the Role
webook.com is seeking a Head of Data to own the data function end-to-end, including strategy, team, platform, and delivery. The role involves building and leading the data team, establishing data governance, and driving data monetisation.
Key Skills for This Role
Responsibilities
- Produce webook’s first documented data strategy and a phased, costed roadmap within 60 days of start
- Define the target operating model for the data function (engineering, analytics, governance) and the sequence in which it is built
- Own the data platform direction; lead the managed vs self hosted decision and present a costed recommendation within 90 days
- Assess, develop and strengthen the existing team; set clear performance bar and build capability
- Set quarterly OKRs for each direct report; hold fortnightly 1:1s; run monthly team standup
- Be accountable for reliable, tested, observable pipelines and client facing dashboards
- Institute FinOps discipline: clear monthly platform budget with alerting
- Establish a single source of truth and a governed metrics/semantic layer
- Build the muscle to ship data products: embedded client analytics, benchmarking, and insight services
- Ensure data handling meets PDPL, GDPR and NCA requirements
- Own the path from internal analytics to embedded client insight to productised data
- Be the trusted data partner to the executive team; drive data literacy and a data as business enabler culture
Requirements
- 10+ years in data, with at least 3 5 years in a senior data leadership role (Head of Data / Director) at a technology, SaaS or consumer platform company
- Proven track record building and leading high performing data teams across engineering, analytics and governance
- Deep, hands on understanding of modern data platforms and the modern data stack: warehouses/lakehouses, transformation (dbt), orchestration, BI, and serving layers
- Experience with open source platforms (ClickHouse, Superset) AND major managed platforms (BigQuery, Snowflake, Databricks)
- Strong command of data engineering and analytics practice: pipelines, dimensional modelling, semantic/metrics layers, data quality and observability
- Demonstrated ability to turn data into business value — ideally including data products or monetisation
- Working knowledge of data governance and privacy in a regulated environment (PDPL/GDPR a strong plus)
- Commercial fluency: able to translate technical work into business and board level language
- A track record of delivering against deadlines
Full Job Posting
Role Overview
- Own webook’s data function end to end strategy, team, platform and delivery and be the single person accountable for data at webook.
- Turn our first party data into trusted decisions today and a monetisable asset within two to three years, in a regulated environment (PDPL / GDPR / NCA ECC).
- Build and lead the team, make the platform reliable, and set webook up to sell data and insight, not just tickets.
What You’ll Own
- Produce webook’s first documented data strategy and a phased, costed roadmap within 60 days of start, endorsed by the VP Architecture, Platform & AI and the CTO.
- Define the target operating model for the data function (engineering, analytics, governance) and the sequence in which it is built.
- Own the data platform direction. Lead the managed vs self hosted decision and present a costed recommendation within 90 days, with a clear cost control model.
- Align every data initiative to a measurable business outcome; re prioritise the roadmap quarterly as the economics move.
- Assess, develop and where needed strengthen the existing team; set a clear performance bar and build the capability to meet it.
- Set quarterly OKRs for each direct report; hold fortnightly 1:1s with written notes; run a monthly team standup with a rolling 90 day delivery view shared with VP Architecture and the CTO.
- Be a genuine people leader: develop talent and career paths, mentor, and build an engaged, high performing team.
- Be accountable for reliable, tested, observable pipelines; client facing dashboards accurate and current, with stale or broken data caught before a client ever sees it.
- Own the platform direction across the modern data stack (warehouse/lakehouse, transformation (dbt), orchestration, BI and serving) — making pragmatic build/buy and managed/self host calls across open source (ClickHouse, Superset) and major managed platforms (BigQuery, Snowflake, Databricks).
- Institute FinOps discipline: a clear monthly platform budget with alerting; own the platform budget and keep cost predictable and under control.
- Establish infrastructure as code, data observability, and clear SLAs for data delivery.
- Establish a single source of truth and a governed metrics / semantic layer; eliminate conflicting metric definitions across the business.
Requirements
- 10+ years in data, with at least 3–5 years in a senior data leadership role (Head of Data / Director) at a technology, SaaS or consumer platform company.
- Proven track record building and leading high performing data teams across engineering, analytics and governance — a genuine people and team leader, not only a technologist.
- Deep, hands on understanding of modern data platforms and the modern data stack: warehouses / lakehouses, transformation (dbt), orchestration, BI, and serving layers.
- Experience with open source platforms (ClickHouse, Superset) AND major managed platforms (BigQuery, Snowflake, Databricks) — able to make pragmatic build/buy and managed/self host decisions with cost firmly in mind.
- Strong command of data engineering and analytics practice: pipelines, dimensional modelling, semantic / metrics layers, data quality and observability.
- Demonstrated ability to turn data into business value — ideally including data products or monetisation.
- Working knowledge of data governance and privacy in a regulated environment (PDPL / GDPR a strong plus).
- Commercial fluency: able to translate technical work into business and board level language.
- A track record of delivering against deadlines — with evidence, not just intent.
- Experience monetising data or building data products sold externally (preferred).
- Familiarity with the KSA and EU regulatory context (PDPL, GDPR, NCA ECC) (preferred).
- Experience making data “AI ready” and enabling ML / analytics at scale (preferred).
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