Job Description
Key Responsibilities
* Design, build and maintain: Conceptual, logical and physical data models to meet business needs of strategic integration via FHIR and analytics OMOP standards with dimensional modelling.
* Define, uphold and validate: Data modelling standards, principles and best practices are met and aligned with business requirements.
* Build, manage and educate: Data catalogues, working closely with data architects and business users to setup and refer to data catalogues.
* Data Quality & Security: Work closely with data architects and data engineers to maintain appropriate security and address data quality issues
* Collaboration & Insights: Partner with analysts, scientists, and business stakeholders to align data modelling alongside delivery of actionable insights and advanced analytics, whilst promoting self service.
* Align modelling to data roadmap: Based on a data domain approach, work alongside the team to develop and plan data modelling to the data and integration roadmap needs, as well as delivery demands.
Required Experience & Skills
* 4+ years in data modelling roles.
* Proven expertise translating business requirements into conceptual, logical and physical data models
* Expertise in data model tools such as ERwin, LucidChart or SQL based platforms to create and manage data structures.
* Proficient coding skills in SQL and database design.
* Experience with CI/CD practices and tools such as Azure DevOps, and data quality frameworks.
* Familiarity with Azure security tools (RBAC, Key Vault) and configuration management.
Desirable Qualifications & Skills
* Certifications: Azure Foundations or Data Scientist Associate, Power BI Data Analyst Associate.
* Experience with FHIR/OMOP data standards, Microsoft Fabric, Microsoft Purview and Power BI would be highly beneficial.
Personal Attributes
* Strong collaboration and communication skills, both inside and outside of technology.
* Passion for quality, innovation, and continuous learning.
* Disciplined focus on improving our data landscape and data modelling practices to minimize overhead of maintenance and maximise re-use.