Data Architect at Inetum2

We are looking for a mid- to senior level Data Architect & Tooling Specialist whose primary mission is to maintain, evolve, and steward our existing data platform. That is a hands on architect who will design, implement, and operate the tooling ecosystem that guarantees the reliability, observability, and compliance of our data platform. The role is heavily weighted toward metadata management, data quality frameworks, CI/CD pipelines, and governance dashboards. The success will be measured by number of data quality incidents, the clarity and completeness of our data catalog, the robustness of governance processes, the adoption of data quality and self-service tools, and the overall transparency of data flows to business users                                                                                                                                                                                                                                           Main Tasks: • Metadata & Semantic Layer, which consists on developing and maintaining the data product catalog, lineage, and metadata standards • Design, implement, and continuously improve a centralized metadata repository • Define and enforce semantic models, particularly business vocabularies, canonical data entities and logical data contracts that translate raw tables into understandable business objects                             • Maintain lineage graphs that are automatically refreshed on each pipeline run • Coordinate efforts with wider bank initiatives related to metadata • Governance, Transparency & Compliance: Provide transparent dashboards for data lineage, access logs, and data quality health that are consumable by business users, auditors, and regulators • Lead quarterly data governance reviews, focusing on data ownership and access • Integrate with broader data governance initiatives                         • Tooling & Automation, which consists on implementing self service data product templates that embed semantic metadata automatically • Introduce observability for data pipelines and lineage updates • Collaboration & Knowledge Sharing, which involves working with domain owners to capture business definitions and map them to technical entities • Conduct regular sessions on metadata best practices • Mentor engineers on embedding semantic annotations