Data Engineering And Operations Advisor 1

Job Description

Roles & Responsibilities

• Design and maintain data models that support analytics, reporting, and operational use cases across Health Services.
• Optimise data models for performance, ensuring they are scalable, efficient, and meet the needs of data scientists, analysts, and downstream consumers.
• Develop and evolve Silver and Gold data layers, embedding holistic business logic and enabling consistent, reusable data assets across the organisation.
• Collaborate with data engineers to ensure accurate ingestion, transformation, and representation of data within the models.
• Work closely with the Data Office, including the Head of Data, Data Science Lead, Data Governance Lead, and BI Team Leads, to align modelling efforts with strategic priorities .
  
  

• Proven experience in designing and maintaining conceptual, logical, and physical data models.
• Strong understanding of data modelling principles, relational databases, and
  
  

• Proficiency in SQL and data modelling tools.
• Experience working with data engineers to ensure accurate ingestion and transformation of data.
• Ability to optimise models for analytical performance and usability by data scientists and analysts.
• Familiarity with developing and managing Silver and Gold data layers to support scalable, reusable data assets.
• Excellent documentation skills, including data dictionaries and metadata repositories.
• Strong collaboration and communication skills, with the ability to work across technical and non-technical teams.
• Previous experience in healthcare or clinical industries, or a strong understanding of operational and customer contexts in Health Services.
• Experience of working with clinical data sets and ontologies to design data models for reporting and analytical use cases as well as a strong understanding of clinical terminologies and its application in health and clinical settings (e.g. ICD-10, FHIR, OMOP)
• Understanding of data governance, privacy, compliance, and regulatory principles and considerations in healthcare.and enterprise data standards.
• Translate complex data requirements into structured models that support data-led transformation and enable actionable insights.
• Document data models, metadata, and data dictionaries to support transparency, governance, and cross-functional understanding.
• Ensure alignment with enterprise data strategy, governance frameworks, and innovation initiatives, acting as a bridge between Health Services and the wider CDAO function.
• Contribute to continuous improvement by evaluating new tools, techniques, and best practices in data modelling and architecture.
• Lead the development and adoption of enterprise-wide data modelling standards and reusable patterns.
• Ensure alignment of data models with enterprise data strategy, governance frameworks, and business transformation goals.
• Mentor junior data modellers and analysts and lead design reviews to ensure modelling consistency and quality