Head of Data

TransferGo is a growing fintech scale-up on a mission to champion financial freedom with care. We strive to provide tailored, more affordable financial services that make people's hard-earned money go further. Now in our 14th year, with close to 400 employees in offices across Europe and the UK, we’re crafting a brilliant, relevant product that makes a difference in people's lives and the well-being of their families. 

We’ve come this far by building a talented, diverse workforce on a fair culture and our strong values. Having this strong team of employees, we can serve those who really need our product to make their lives better. 

This role is designed for a "Hub-and-Spoke" organizational model. The Head of Data will not manage the day-to-day tickets of embedded analysts but will own the Data Strategy, Infrastructure, and Standards that allow those analysts to be successful and consistent across the company.

 

Role Mission

As the Head of Data, the mission is to transform a decentralized data landscape into a unified, high-performance ecosystem. Head of Data will bridge the gap between autonomous product squads and a centralized data vision. Head of Data is the architect of our data culture, ensuring that while analysts sit within different business units, they operate with a common language, world-class tools, and uncompromised data integrity.

 

Key Responsibilities

Strategic Leadership & Governance

• Unified Data Strategy: Define and execute a global data roadmap that aligns with company-wide OKRs.
• Standardization: Define universal metrics (e.g., "Active User," "Revenue") to ensure a single source of truth across all departments.
• Data Governance: Set policies for data privacy, security, and compliance (GDPR) without bottlenecking the speed of the product teams.

Platform & Infrastructure

• Modern Data Stack: Own the selection and maintenance of our data warehouse (e.g., Snowflake/Redshift), transformation layers (dbt), and BI tools (Looker/Tableau).
• Data Engineering Oversight: Lead the core data engineering efforts to ensure a robust ETL/ELT pipeline that serves the decentralized "spokes."
• Self-Service Enablement: Build the infrastructure that allows non-technical stakeholders to access insights without needing an analyst for every query.

Functional Excellence & Community

• The Data Guild: Create and lead a "Data Guild" or "Community of Practice" to facilitate knowledge sharing, peer reviews, and mentorship among embedded analysts.
• Talent Bar: Define the hiring standards, leveling rubrics, and career paths for all data roles across the company. 
• Best Practices: Drive the adoption of version control (Git), documentation, and automated testing (Data Quality) within the analytic workflows.

Business Impact & Culture

• Data Literacy: Act as an evangelist for data-driven decision-making, coaching C-suite and Product Leads on how to better leverage data.
• Resource Allocation: Partner with Department Leads to identify where data gaps exist and advocate for the placement of analysts in the highest-impact areas.

 

Key Requirements

Strategic Leadership & Organizational Design

• Architectural Strategy: 6+ years of experience in Data/Analytics, with a proven track record of scaling "Hub-and-Spoke" or Data Mesh models. Demonstrated ability to balance centralized governance with decentralized execution speed.
• Strategic Influence: Proven ability to influence and align senior stakeholders (C-level, Product Leads) who do not have a direct reporting line to this role. Ability to lead through expertise and professional authority.
• Data-as-a-Product Mindset: A strategic approach to treating the data platform, tooling, and core datasets as internal products, where embedded analysts and business units are the primary customers.
• Change Management: Experience in leading organizational transitions (e.g., from centralized to decentralized) and establishing a high-performance data culture across distributed teams.

Technical Excellence & Methodology

• AI Modernization & Tooling: Lead the evaluation and strategic implementation of cutting-edge AI-driven data extraction solutions, ensuring selected technologies align with cross-depart