Director of Data

Stack

Responsibilities

• ▹Lead the teams that own the three pillars of data (data engineering, data analytics, data science), bringing them into a unified org while respecting their specialised skills
• ▹Ensure the Data org operates as a Centre of Excellence, supporting and educating the customers of data across the business
• ▹Break down silos and form strong working relationships with stakeholders
• ▹Define and shape a data strategy fit for purpose across analytical and agentic business needs
• ▹Own data governance and quality: establish the policies, standards, ownership model and forums that make data trustworthy; manage day-to-day compliance with GDPR and emerging AI regulation and set practical guardrails for data and AI use
• ▹Sponsor the data platform: work with engineering and architecture to maintain a reliable, performant, cost-aware platform across ingestion, storage, transformation, BI and ML; make build/buy/partner recommendations and manage key vendor relationships
• ▹Scale analytics and AI capability: define how use cases are sourced, prioritised, productionised and governed; curate a portfolio balancing quick wins, strategic bets and long-term capability building; champion self-service BI without losing control of metrics and a single source of truth
• ▹Partner across the business: build strong working relationships with leaders in every function, translate technical choices into commercial language and resolve cross-functional disputes over data ownership and priorities

Requirements

• ▹7+ years in data, analytics or related disciplines, including 3+ years leading teams that span more than one sub-discipline (e.g. engineering and analytics, or analytics and science)
• ▹Has shaped and delivered a data strategy for a business
• ▹Has worked inside, built or substantially evolved a CoE-style or shared-services function: service model, hub-and-spoke design, intake and prioritisation
• ▹Strong working knowledge of modern data architecture: warehouse/lakehouse patterns, streaming, orchestration, BI and the basics of GenAI; cloud platform fluency (AWS / GCP / Azure) sufficient to challenge decisions
• ▹Hands-on accountability for data governance, quality and regulatory compliance (GDPR at minimum)
• ▹Experience supporting GenAI use cases and setting a strategy that supports productisation
• ▹Proven ability to partner with department heads and VP-level leaders across functions
• ▹Owns and defends a budget; builds business cases with realistic benefits and ranges of uncertainty; manages vendor relationships pragmatically
• ▹Hires, develops and retains managers and senior individual contributors
• ▹Strong written and verbal communication

Nice to have

• ▹Experience in a high-growth or scale-up environment where the data function had to be built or significantly reshaped
• ▹Background in industries with operational complexity, real-time data needs, or supply chain / logistics / marketplace dynamics
• ▹Hands-on past as a data engineer, analytics engineer or data scientist
• ▹Experience implementing a data mesh or federated data product model
• ▹Familiarity with the EU AI Act and emerging AI governance frameworks
• ▹Experience evaluating, procuring and rolling out AI tooling (LLMs, coding assistants, analytics copilots) at organisational scale, including licensing and policy
• ▹Track record of contributing to public technical discourse: conference talks, writing, open source or community involvement
• ▹Graduate qualification in a quantitative, computer science or related discipline
• ▹Multi-language working environments and experience operating across European or global teams

Soft skills

About the company

Forto harnesses the power of AI to revolutionise logistics. It wants to reinvent digital supply chains to be transparent, frictionless and sustainable, and to simplify global trade.