Data Architect

Job Description

• Establishes the rules for describing and completing a data valuation process for data objects. Creates ecosystem models (e.g. logical, canonical) that are required for supporting services within the enterprise data architecture.
• Prepares data models; designs information structure & data flow; designs & validates ETL maps.
• Ensures regulatory issues are considered surrounding information assets.
• Recognizes and resolves conflicts between models, ensuring that data models are consistent with the ecosystem model (e.g., entity names, relationships and definitions).
• Ensures integration of the project logical data model into the ecosystem conceptual data model.
• Ensures that physical models align with the logical data model.
• Creates a framework for representing the data elements including entities, relationships, attributes.
• Guides the implementation of a self-service and end-to-end BI solution to enable business insights.
• Design of Data models in the Transactional Systems aligned to Information Architect advisory.
• Defines database technology (e.g.: MS SQL, Oracle DB, Data Lake...) most suitable to host the data in each initiative.
• Defines Data Test Strategy in projects;
• Partners with Data & Analytics group to advise about Data Models
• Is recognized as an expert in Data Warehouse, Business Intelligence area. Biotech / Pharma experience and TOGAF certification is a plus.
• Exhibits strong soft skills typically required as an Architect (i.e.: presentation and public speaking, negotiation, challenging the status quo)
• Exhibits an Agile mindset, i.e. Good enough instead of perfection and Focus on "Reuse before Buy before Make" when providing direction on future solutions
• Is a good team player in a global environment.
• Has practical experience in Business Intelligence data architecture - to suggest when using tabular structures, star schemes, views and extracts.
• Has practical experience and knowledge of Big Data platforms - to suggest the best technology for storing and making data available: Oracle database, Hadoop (Cloudera, Hive, Impala).
• Has Practical experience and solid knowledge on ETL tools: Alteryx and Informatica PowerCenter
• Has practical experience and solid knowledge on Business Intelligence & Data Visualization tools: Tableau.
• Experience setting up data sharing agreements
• Good understanding of data input & output formats - APIs, extracts, user inputs etc
• Experience defining observability rules and mechanisms
• Experience in Insights, Data Products and Data Mesh Concepts and Information Architecture and Modeling