Senior Data Vault 2.0 Lead/Enterprise Data Warehouse Owner

Project overview

An excellent freelance opportunity to take ownership of a strategic enterprise data platform, influence data architecture decisions, and work closely with multidisciplinary teams to drive the evolution of a modern, scalable and business-oriented data environment.

Project details

Brussels

Hybrid: 3 days per week onsite

Language: English (mandatory); Dutch or French advantageous

The Opportunity

Are you an experienced Data Vault 2.0 specialist passionate about enterprise data architecture, data governance and enabling business-driven data solutions?

We are looking for a Senior Data Vault 2.0 Lead/Enterprise Data Warehouse Owner to take ownership of a Corporate Structured Layer within a complex, enterprise-scale data environment.

In this role, you will be responsible for the integrity, scalability and business value of an Enterprise Data Warehouse built on Data Vault 2.0 principles. Combining hands-on technical expertise with collaborative leadership, you will oversee a highly automated, metadata-driven ETL environment while supporting and coaching domain teams in data modelling, onboarding and best practices.

Acting as the bridge between business stakeholders and technical delivery teams, you will play a key role in driving consistent data architecture, improving data quality and strengthening enterprise-wide adoption of Data Vault methodology.

Key Responsibilities

Enterprise Data Warehouse Ownership

Domain Team Enablement & Collaboration

Data Architecture Advocacy & Governance

Essential Technical Experience

Desirable Experience

Personal Attributes

Education & Languages

Looking forward to receiving your application!

• Own and govern the Corporate Structured Layer, ensuring scalable and consistent Data Vault 2.0 architecture.
• Design, optimise and maintain Hubs, Links and Satellites in line with business requirements and enterprise standards.
• Oversee metadata-driven ETL pipelines built using Spark.
• Monitor data quality, integrity, lineage and loading processes across the data platform.
• Work closely with Data Engineers and DevOps teams to troubleshoot and optimise pipeline performance.
• Establish and enforce data modelling standards, naming conventions and architectural best practices.
• Coach and support domain teams across areas such as Risk, Finance and Customer Data.
• Provide guidance on Data Vault 2.0 fundamentals, modelling techniques and implementation practices.
• Facilitate collaborative modelling sessions to align domain-specific requirements with the enterprise data architecture.
• Advise on source-to-target mappings, business key design and satellite strategies.
• Develop documentation, templates and training materials to accelerate adoption.
• Act as a Data Vault 2.0 ambassador, promoting best practices and demonstrating the benefits of scalability, flexibility and auditability.
• Drive consistent adoption of enterprise data modelling standards.
• Ensure compliance with data governance policies, GDPR and internal audit requirements.
• Contribute to data catalogue and metadata management initiatives.
• Keep up to date with Data Vault 2.0 developments, automation solutions and industry best practices.
• Minimum 3 years of hands-on experience with Data Vault 2.0, including modelling, implementation or governance.
• Strong SQL skills, including complex queries and performance optimisation.
• Practical experience with Apache Spark, PySpark and/or Spark SQL.
• Familiarity with Oracle Exadata and cloud object storage solutions such as IBM Cloud Object Storage or S3.
• Experience working with metadata-driven ETL pipelines.
• Understanding of data lineage, metadata management and enterprise data architecture.
• Experience with data modelling tools such as Erwin or PowerDesigner.
• Familiarity with data catalogue platforms such as Collibra or Alation.
• Knowledge of financial services or banking data domains, particularly Customer, Finance, Transactions or Risk.
• Data Vault 2.0 certifications (eg CDVP2) or relevant data modelling qualifications.
• Strong communication skills, with the ability to translate complex technical concepts into business language.
• Collaborative mindset and experience working with cross-functional teams.
• Passion for mentoring and supporting teams in adopting Data Vault best practices.
• Strong analytical and problem-solving capabilities.
• Comfortable working in an Agile, DevOps and squad-based environment.
• Proactive approach to identifying improvements and driving technical standards.
• Bachelor's or Master's degree in Computer Science, Data Engineering, Economics or a related discipline.
• Fluent English is mandatory.
• Dutch and/or French would be a strong advantage.
• Start: ASAP
• Duration: 12 months
• Remote: hybrid
• Location: Brussel, Belgium, BE
• Languages: English