Responsibilities:

• Perform functional and non-functional system testing of the Health Data Utility (HDU)
  
• Provide ongoing testing for the routine and incident management of HDU
  
• Test bug fixes in reporting as per defects found by business and as per HDU IRC project
  
• Create complete system testing documentation and artefacts, including test plans, test cases, test scripts, automated test scripts, test results reports, defect logs
  
• Transform functional, business, and system knowledge into effective test case planning and execution.
  
• Create test data according to the test plan; analyze testing results and retesting until expected results are obtained; perform reviews with users and ensures client acceptability levels are met (e.g. participating in walk throughs); recommend changes to ensure acceptable testing results; retest all criteria in a live environment and recommend user sign off for implementation.
  
• Work closely with developers, architects, product owners, and others in establishing effective test plans based on feature documentation.
  
• Apply QA and technical expertise and engage other expertise to track and resolve testing and production issues and other IT related problems with quality deficiencies and maintain client service integrity.
  

MUST HAVES:

7+years experiences in the following:

• developing conceptual, logical and physical data models for structured, semi-structured, and unstructured data with relational, star and snowflake schemas.
  
• Proficiency in data modeling methods and tools (e.g. ERWIN, VISIO, Power Designer).
  
• developing and implementing common data models and master data management strategies
  
• design schemas that balance agility, schema flexibility, data governance, and quality.
  
• Expertise in creating schemas that allow flexible querying and analysis across various data formats.
  
• defining data partitioning, clustering, and indexing strategies to optimize query performance and data access patterns.
  
• implementing schemas and metadata structures that support efficient data management.
  
• Understanding of data governance principles and practices, especially in designing schemas and metadata structures.
  
• Experience in creating Architecture Artefacts based on enterprise standards.
  
• 4+ years experience in designing schemas that integrate diverse data types stored in a data lake or data lakehouse.
  
• 3+ years experience of implementing Medallion architecture or similar frameworks. Familiarity with tools and techniques for managing metadata in a data lakehouse environment.
  
• Hands-on experience with Azure services, including Azure Data Factory, Azure Data Lake Storage, and Azure Databricks
  
• 10+ years experience with Solutions development.
  
• Experience in addressing complex data integration challenges and design efficient, scalable data models.
  
• Experience in monitoring and enforcing data modelling/normalization standards.