Head of Data Management

Michael Bailey Associates; Randstad; On-site; EUR 90,000 - 130,000; Full time

Job summary

A global technology organization seeks a senior engineering leader in Flevoland, Netherlands to define and scale a unified Data → Knowledge → Skills platform. Responsibilities include defining architecture, ensuring data governance, and leading cross-functional collaboration. The ideal candidate has over 15 years in data engineering, strong leadership skills, and experience with multi-region environments. This role emphasizes a product-oriented approach to enhance usability and decision-making across analytics and AI-driven initiatives.

Qualifications

• 15+ years in data or platform engineering.
• 5+ years in leadership roles in multi-region environments.
• Proven record building modern data platforms including knowledge layers.

Responsibilities

• Define and own the architecture of a multi-layered data platform.
• Establish frameworks for data quality, lineage, and compliance.
• Design and operationalize a governed semantic layer.

Skills

Data governance

Data quality assurance

Cross-functional collaboration

Technical leadership

Product mindset

Tools

Databricks

Job description

Role Overview

A global technology organization is seeking a senior engineering leader to define, build, and scale a unified Data → Knowledge → Skills platform. This platform underpins analytics, AI-driven decision-making, and operational automation across a multi-region business.

This is a product-oriented platform leadership role, responsible for transforming data infrastructure into a governed, reusable system that enables both human users and AI systems to reason, act, and execute consistently.

Key Responsibilities

Platform Architecture & Strategy

• Define and own the architecture of a multi-layered platform consisting of:
• Data Layer: Governed, high-quality datasets (transactional, event-driven, dimensional, feature stores)
• Knowledge Layer: Semantic models including business metrics, entity relationships, and contextual definitions
• Skills Layer: Reusable operational capabilities such as APIs, workflows, pipelines, and agent-enabled tools
• Ensure scalability, reliability, and interoperability across all layers

Data Governance & Quality

• Establish robust frameworks for data quality, lineage, observability, and compliance
• Standardize and enforce auditable business metric definitions
• Ensure datasets are clean, trusted, and fully queryable across use cases

Semantic & Knowledge Systems

• Design and operationalize a governed semantic layer
• Enable consistent interpretation of business metrics across stakeholders and systems
• Support both human analytics and machine reasoning through structured knowledge models
• Drive a platform-as-product approach, focusing on usability, adoption, and developer experience
• Build reusable capabilities including:
• APIs and services
• Analytical workflows
• Orchestration frameworks
• Define and manage SLAs/SLOs with measurable performance outcomes
• Lead the design of data localization and residency architectures across multiple jurisdictions
• Balance regulatory compliance requirements with a unified global data model
• Ensure consistency in definitions and metrics across regions

Cross-Functional Collaboration

• Partner with teams across:
• Data Science and AI Engineering
• Product and Engineering
• Risk and Compliance
• Enable rapid experimentation, automation, and high-quality decision-making

Candidate Profile

Experience

• 15+ years in data or platform engineering
• 5+ years in leadership roles within complex, multi-region environments
• Proven track record building modern data platforms beyond storage, including semantic or knowledge layers

Technical Expertise

• Strong background in:
• Data governance, lineage, and observability
• Lakehouse architectures (e.g., Databricks or equivalent)
• Experience designing semantic layers or knowledge systems
• Experience building programmatic and reusable data capabilities (APIs, workflows, tools)

Strategic Capabilities

• Experience implementing data localization and regulatory-compliant architectures
• Strong understanding of privacy and governance in multi-jurisdictional environments
• Product mindset with focus on adoption, usability, and measurable impact

Leadership Attributes

• Ability to operate at both strategic and hands-on levels
• Strong cross-functional collaboration skills
• Track record of building and scaling high-performing engineering teams

Success Metrics

• Adoption and usability of the platform across technical and business stakeholders
• Consistency and reliability of business metrics and semantic definitions
• Reduction in time-to-insight and improvement in decision qualityScalability and compliance of global data architecture
• Effectiveness of AI-enabled workflows and automation capabilities