Head of Data Solution

Data is a key part of AXA’s journey “from Payer to Partner”, and the transformation of the organisation as a Data Driven company. To succeed in this journey, AXA Partners Data Strategy has been organised around 6 pillars: Enable Business initiatives, Protect Data, Organize and Govern initiatives, Manage Data, Empower People on Data, Deliver and operate Data Platforms.

As the Head of Data Solution, you will act as the technical and organizational leader—a "Chapter Lead"—for a talented, multi-national team of approximately 10 Data Engineers and Data Analysts. Your primary mission is to orchestrate the delivery of robust, maintainable, and high-value data solutions that drive business priorities. This role requires a unique blend of deep technical expertise, strategic solution design, and inspiring people leadership. You will be the guarantor of the quality and reliability of all solutions developed by your team, ensuring they align with AXA Partners' data-driven transformation goals.

What you’ll be doing:

Team Leadership & Capability Building

• Steer and develop a distributed team of data professionals across Spain, France and UK, fostering a culture of excellence and accountability
• Lead, mentor, and manage the day-to-day operations of the Data Solution team across three countries.
• Build technical capabilities across the team in Azure Databricks, PySpark, SQL, and modern data practices through structured guidance and knowledge-sharing.
• Foster a collaborative and engaging team environment that leverages individual areas of expertise.
• Prioritize work and delegate effectively, fostering ownership within the team while retaining ultimate accountability for all deliveries.

Strategic Technical Partnership & Solutioning

• Act as the primary technical partner to the Global Product Owner (GPO), translating business requirements and strategic goals into robust and feasible technical solutions.
• Advise on technical feasibility, development effort, and architectural best practices to help prioritize the analytics roadmap.
• Propose the best technical solution for each business need, ensuring alignment with long-term strategy and platform capabilities.

Technical & Architectural Ownership

• Provide expert technical guidance to the team, challenging and validating the design of data solutions before development begins.
• Define, implement, and enforce development best practices for version control (Git), documentation, and coding standards.
• Organize and conduct regular code reviews to ensure quality, performance, and maintainability.
• Act as the ultimate guarantor for the reliability and robustness of all data solutions delivered by the team.

Financial Management & FinOps

• Define the team's technical roadmap, enforce best practices, and own the team's cloud cost footprint (FinOps) to balance performance with efficiency.
• Own and optimize the team's cloud cost footprint across Azure and Databricks.
• Drive a cost-awareness culture within the team to balance performance with efficiency.
• Report on spend trends and optimization efforts to leadership.

Accountable Innovation & Governance

• Foster a culture of responsible innovation, encouraging the team to explore and pilot emerging technologies, including the pragmatic use of Generative AI.
• Ensure that while experimenting, the team remains accountable for the quality and timeliness of their deliveries.
• Ensure all delivered solutions adhere to the data governance, security, and compliance standards defined by Data Domain Owners and the Central Data Office.
• Follow and influence these governance policies by providing technical feedback and embedding them into the development lifecycle.

What you’ll bring:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field is preferred.
• About 8 years of experience in the data field.
• Demonstrated experience leading technical teams (e.g., as a Chapter Lead, Tech Lead, or Data Manager), managing distributed, multi-cultural teams.
• Cloud & Big Data Expertise: Expert-level proficiency in the Azure data stack, particularly Azure Databricks, with strong, hands‑on skills in PySpark and SQL.
• Business Intelligence: Strong working knowledge of Power BI architecture, performance optimization, and design best practices. Able to review and guide BI solutions for quality and maintainability.
• Data Architecture: Solid understanding of data warehousing principles, dimensional modeling (Kimball, star schema), and modern data architecture patterns.
• Software Engineering Mindset: Strong command of software development best practices, including version control (Git), CI/CD pipelines, and automated testing.
• Strategic Partnership &