Job Responsibilities:

• 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.

  Job Requirements:

• 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.

• 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.

• Has practical experience in unstructured data management.

• Experience on AWS and Azure data lake & analytics platforms is a strong plus.

• Experience in patient data management and HCP/HCO data management is a strong plus.

• Experienced with different data modelling techniques (Relational, Dimensional, Data Vault, etc.)

• Demonstrates good understanding of data privacy & security regulations, for example GDPR