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KIABI

Low-cost family fashion retailer worldwide

Data Platform Manager

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeLezennes, FranceIn-person

About the Job

Requirements

  • A Bac+5 qualification in computer science, data science, engineering school, or equivalent is required.
  • At least 7 years of data engineering experience, including initial experience in technical management or facilitating an engineering collective, is required.
  • Strong command of a modern cloud data stack is required, ideally Google Cloud Platform (GCP), including BigQuery, Dataform, Cloud Composer, and Cloud Build.
  • Confirmed DevOps/DataOps culture is required, including CI/CD with GitLab, Infrastructure as Code with Terraform, and observability with Dynatrace.
  • Knowledge of modern data architectures is required, including Lake House, Data Lake, Data Warehouse, and Data Mesh.
  • Sensitivity to SecOps and FinOps is required, including access governance, security, and management and optimization of cloud costs.
  • The candidate should demonstrate technical and cross-functional leadership, business-value orientation, ability to arbitrate between technical and business needs, clear and structured communication, documentation practices, and a facilitator or servant-leader approach.
  • The candidate should be comfortable in architecture reviews and discussions with business stakeholders.

Responsibilities

  • Define the data platform vision, roadmap, and target architecture for a 2-to-3-year horizon, including Lake House, Data Lake, Data Warehouse, and Data Mesh approaches.
  • Prioritize use cases according to business impact and DataTeam needs, balancing technical debt, performance, and new features.
  • Manage the product backlog and delivery using the Scrum agile methodology.
  • Define and maintain engineering standards for pipeline patterns, environment management, and test strategies covering unit tests, integration tests, and monitoring.
  • Lead the cloud strategy on GCP, including sizing, access governance with IAM, security, and encryption.
  • Ensure good practices for CI/CD, automation, observability, and solution monitoring.
  • Improve Data Engineer productivity through tooling, templates, technical documentation, and onboarding.
  • Manage critical level-4 incidents and ensure service continuity; coordinate with the Continuous Improvement & Operations Manager so every Sifflet, infrastructure, and pipeline alert receives either immediate correction or a continuous-improvement action in the backlog.
  • Design and operate platform foundations for LLM and RAG services and AI agents, including an agent registry, multi-agent orchestration, vector memory, and observability.
  • Define integration patterns between AI agents and internal data sources, including BigQuery, Firestore, and business APIs, with traceability and governance.
  • Improve the reliability, security, and scalability of agent-based use cases, including performance, cost, and monitoring.
  • Conduct proofs of concept on emerging technologies such as Vertex AI, agent frameworks, and Feature Store, and monitor cloud developments.
  • Supervise experts in the Data Components squad and support Data Engineers through recruiting, skill development, objectives, interviews, and team rituals.
  • Facilitate the cross-functional Back Engineering chapter by building consensus, clarifying choices, enabling discussion, and ensuring collective decisions are understood.
  • Prepare and facilitate chapter meetings, document decisions and open issues, track execution, and ensure decisions are relayed to squads through ambassadors.
  • Escalate persistent blockers to the Data & AI Components Leader with available options and the nature of the disagreement.
  • Produce chapter deliverables, including meeting minutes within 48 hours, a living chapter backlog, and a standards roadmap.
  • Track platform adoption and usage and ensure components are accessible and usable across Kiabi Group teams, including France, Asia, independent business units, and detached services.
  • Ensure satisfaction among platform users, including Data Engineers and business squads, and deliver measurable value.

Desired Qualifications

  • Experience with or strong interest in generative AI and agentic architectures, including LLM, RAG, Vertex AI, and multi-agent orchestration, is a major advantage.
  • Google Cloud Platform (GCP) is the preferred cloud platform.

About the Company

KIABI

Low-cost family fashion retailer worldwide

KIABI offers affordable fashion for the whole family, with a focus on low-cost ready-to-wear. Its product lines are designed in France by an in-house team of 56 fashion designers, and the company sells through a network of more than 505 shops worldwide. The fashion ranges are created in-house and then produced to be accessible and easy to wear for people of all ages and nationalities. The company operates with a straightforward business model: make simple, universal clothing at low prices and keep costs down by managing design in-house and selling through a large retail network. Compared with competitors, KIABI stands out thanks to its large global presence, French design origin, and emphasis on universality and joie de vivre in its branding, aiming to be the go-to source for affordable family fashion. Its goal is to keep fashion accessible for everyone while growing its international reach and maintaining French design sensibilities.

Company size
10,001+
Company stage
Not listed
Total funding
Not listed
Headquarters
Hem, France
Founded
1978

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