CIO (Data-driven)

Recruiting a CIO (Data & AI-driven) requires a thorough understanding of their role. The following is a very general summary, which should be adapted to your specific context.

The CIO (Data & AI-driven) is the strategic leader responsible for modernizing IT infrastructure and aligning it with the needs of data and AI transformation. Their primary mandate is to drive the transition to an agile, cloud-native, and data-centric IT architecture, capable of supporting large-scale data science, AI, and analytics initiatives.

They oversee both IT infrastructure modernization (cloud migration, DevOps, security) and data platform management (IaaS/PaaS), ensuring that systems are scalable, secure, and aligned with business objectives.

Responsibilities and Missions

1. Define and Drive IT and Data Modernization Strategy

Develop a roadmap for IT transformation (cloud, agility, data-centric).
Align IT infrastructure with the needs of data and AI teams.
Define technical standards for data platforms (IaaS/PaaS).
Collaborate with management to prioritize IT and data investments.

2. Modernize IT Infrastructure for Cloud and Data

Lead migration to cloud (AWS, Azure, GCP) and hybrid architectures.
Implement DevOps and FinOps practices to optimize costs and performance.
Modernize legacy systems to make them compatible with data-driven needs.
Ensure infrastructure security and compliance (GDPR, ISO 27001).

3. Design and Manage the Data Platform (IaaS/PaaS)

Architect a scalable data platform (data lake, data warehouse, data mesh).
Select and deploy appropriate technologies (Snowflake, Databricks, etc.).
Optimize data platform costs and performance.
Ensure seamless integration with analytics and AI tools.

4. Federate IT and Data Teams

Align IT, data engineering, and data science teams on a shared vision.
Define collaboration processes between technical teams.
Promote a data-driven culture within the organization.
Manage upskilling and training programs to support the transformation.

5. Ensure Data Security and Governance

Implement governance policies (data quality, lineage, metadata).
Guarantee data security (encryption, access control, audit).
Define compliance frameworks (GDPR, data sovereignty).
Oversee risk management related to data and AI.

6. Drive Innovation and Technology Partnerships

Monitor latest advancements (cloud, data, AI).
Evaluate and select technology partners (cloud providers, vendors).
Lead Proofs of Concept (PoCs) to validate innovative solutions.
Represent the company in tech ecosystems (conferences, consortia).

Examples of Concrete Achievements

Led full migration to AWS cloud, reducing infrastructure costs by 30% while improving scalability.
Designed and deployed a unified data platform (Snowflake + Databricks), reducing data access times by 40%.
Modernized legacy systems for AI compatibility, cutting processing times by 50%.
Implemented complete data governance (Collibra), improving data quality by 35%.
Negotiated strategic partnerships with major cloud providers, lowering costs by 20%.