Data Platform Engineer (Data & Metadata Modelling)

Position Overview

We are seeking a Data Platform Engineer (Data & Metadata Modelling) to lead the development, management, and automation of enterprise metadata and data modelling frameworks. The ideal candidate will have deep expertise in international data modelling standards (e.g., SDMX, DDI) and associated tooling (such as FMR and SDMX Matrix Generator). This role is instrumental in enabling data interoperability, metadata quality, and efficient data lifecycle management across platforms.

Key Responsibilities

Data & Metadata Modelling

• Design and implement data models aligned with international metadata standards (SDMX, DDI, DCAT, etc.)
• Collaborate with data architects, domain experts, and standards bodies to maintain semantic consistency
• Develop and maintain SDMX artefacts (data structures, codelists, dataflows, mappings)
• Ensure high metadata quality, consistency, and validation using industry-standard tools
• Support the adoption and integration of metadata registries across the organization

Metadata Tooling & Automation

• Operate and extend tooling for metadata modelling, including SDMX Matrix Generator, FMR, and related libraries
• Develop scripts and utilities to automate metadata generation, validation, and transformation
• Integrate metadata tooling with data pipelines and data catalog platforms
• Contribute to the development of custom plugins, connectors, and APIs for SDMX/DDI tools

Platform Integration & Lifecycle Management

• Integrate metadata models with enterprise data platforms and business intelligence tools
• Manage the versioning, publishing, and governance of metadata artefacts
• Support the deployment of metadata services in cloud-native environments (e.g., Kubernetes, Docker)
• Ensure compatibility with evolving data platforms, APIs, and reporting systems

Governance & Quality Assurance

• Enforce metadata governance policies and support compliance with open data standards
• Conduct peer reviews, documentation, and metadata audits for continuous improvement
• Provide training and support for internal teams on SDMX/DDI standards and tools
• Participate in cross-functional working groups on metadata strategy and standardization

Required Qualifications

Technical Skills

• 6+ years of experience with data and metadata modelling, ideally in public sector, statistical, or research environments
• Strong expertise in SDMX (Statistical Data and Metadata eXchange) and DDI (Data Documentation Initiative)
• Hands-on experience with SDMX Matrix Generator, FMR (Fusion Metadata Registry), and related tools
• Familiarity with metadata registries, ontologies, and semantic modelling
• Proficient in XML, RDF, JSON, and associated schema definitions (XSD, SHACL)

Engineering & DevOps Skills

• Experience with automation and scripting (Python, XSLT, Bash) for data transformation and validation
• Familiarity with version control (Git), CI/CD workflows, and containerization (Docker)
• Understanding of metadata APIs and integration with data platforms or catalogs
• Exposure to data exchange standards (DCAT, SKOS, OWL) and interoperability best practices

Preferred Qualifications

• Bachelor's or Masters degree in Information Science, Computer Science, or related field
• Experience working with statistical agencies, open data portals, or international data organizations
• Knowledge of data governance frameworks and FAIR data principles
• Experience with cloud-native environments (AWS, Azure, GCP) and metadata services
• Participation in international working groups or standardization bodies (e.g., SDMX Technical Group)