Head of Data

Quick Facts

• Role: Head of Data

• Focus: Data strategy, governance, data platform leadership (Databricks), and advanced analytics/AI

Description

Lead and execute the organization’s data strategy and enable data-driven decisions. You will manage data teams across analytics, data engineering, and data science, partnering with senior stakeholders to turn data into better customer experience, smarter product management, and overall improved company performance.

Responsibilities

• Define and deliver the organization’s data strategy and align it with the group’s direction

• Support better decision-making with data and identify growth opportunities (revenue, profitability, CX)

• Bring insights to leadership and move the organization toward data-driven operations

• Own data governance (quality, ownership, catalog, compliance) and ensure data is reliable and secure

• Lead development of a modern data platform using Databricks; decide on architecture and tooling

• Ensure the data stack is scalable and efficient and fits the group context

• Drive advanced analytics and AI use cases (pricing, fraud, churn, personalization) into everyday business

• Lead and grow analytics, engineering, and data science teams; set up an operating model

• Bridge business, IT, and analytics—translate needs into concrete solutions

• Serve as a key partner to CEO, CFO, CRO, CMO, and group leadership (especially the group CDO)

Requirements

• 8–12+ years of data experience, including several years in a leadership role

• Experience creating and executing a data strategy

• Ability to operate in a multi-company/matrix environment and align a shared direction

• Strong business mindset (ideally finance, insurance, telco, or e-commerce)

• Knowledge of data architecture: Databricks, dbt, DWH, Airflow, data lakes, pipelines

• Experience with BI tools (Power BI, Metabase)

• Strong SQL skills and comfort with cloud (Azure, AWS, or GCP)

• Experience leading a multidisciplinary team

Benefits

• Real impact on insurer operations and the group

• Opportunity to influence data strategy, technology choices, and how teams work with data

• Space to build from the ground up and continue improving

• Cross-group collaboration and knowledge sharing

• A direct environment where good ideas are implemented