Timestamp Group aggregates several leading Portuguese IT solutions and services companies around the concepts of excellence and knowledge sharing. We are committed to technological leadership, based on the quality of our service and technological solutions, supported by continuous training and certification.Role: Data ArchitectExpertise:Azure Databricks: The candidate should have in-depth knowledge of Azure Databricks, including setting up clusters, notebooks, and jobs. Familiarity with Spark-based data processing and ETL pipelines is essential.Unity Catalog: Proficiency in managing data using Unity Catalog within Azure Databricks. Understanding catalog objects, schemas, and permissions is crucial.Data Governance and Security: Ability to enforce data governance policies using Unity Catalog, including managing access controls, permissions, and data lineage. Knowledge of security best practices, encryption, and compliance standards.Metastore Administration: Experience as an Azure Databricks metastore admin or familiarity with metastore management. Understanding of how to create and manage catalogs in Unity Catalog linked to the workspace.Catalog Creation and Management: Proficiency in creating and managing catalogs within Unity Catalog, including understanding the CREATE CATALOG privilege and ensuring compliance with Unity Catalog access modes.Workspace Administration: Ability to configure and enable Unity Catalog for Azure Databricks workspaces, including assigning roles and permissions to users.Collaboration and Communication: Strong communication skills to collaborate with data engineers, data scientists, and other stakeholders. Ability to document processes, guidelines, and best practices related to Unity Catalog and Databricks usage.Responsibilities:Model business requirements - data strand - in a standardized, denormalized, star, or other standard data model according to objectives.Model business requirements in a data model beyond the tabular: columnar, graph, geographic, time series, document.Apply reference data architectures according to the requirements of the data management strategy.Evaluate blueprint for organizational data framework defined how data is obtained, stored, consumed, integrated, and managed in order to enrich the company's DataLakes, MDU, and Datamarts.Define indicators inherent to DataOps observability organized into aspects of data-level health (profiling within 'expectation envelope', outlier and anomaly detection, data drift and business rule enforcement).Place: Lisbon (hybrid)Start: ASAP#J-18808-Ljbffr