Senior Data Analytics & Data Modelling Specialist

We are looking for an experienced Senior Data Analytics & Data Modelling Specialist to help shape and evolve governed data models and analytical solutions within a complex pharmaceutical and life sciences environment.

In this role, you will bridge the gap between real-world business requirements, complex datasets, data governance, and technical implementation. You will analyse and model real-world data, translate business use cases into governed entity models, and ensure that platform capabilities are developed around genuine business and data needs.

You will work closely with data governance, business, analytics, and engineering teams to establish high-quality, reusable, and well-governed data assets.

• Analyse complex real-world datasets and design governed entity models based on entities, properties, relationships, cardinality, grain, and underlying data structures.
• Translate business requirements and real-world use cases into clear data requirements and governed data models.
• Represent the demand side of the data platform, ensuring that platform capabilities address genuine business needs and analytical use cases.
• Perform data profiling, data mapping, data quality assessments, and gap analyses to identify data issues, inconsistencies, and improvement opportunities.
• Collaborate with data governance teams on data ownership, business definitions, metadata, lineage, quality standards, and governance processes, ensuring models adhere to established standards.
• Work with engineering teams to translate conceptual and business requirements into technically viable solutions, utilising command-line tools and YAML-based configuration management.
• Contribute to the evolution of the organisation's data platform and modelling standards.

• 8+ years' experience in Data Analytics or Data Engineering
• Proven expertise in data modelling, data governance, and translating business requirements into governed entity models, including data profiling, mapping, quality assessment, and gap analysis
• Strong understanding of entity relationships, cardinality, grain, and data structures; ability to convert real datasets into governed entity model instances
• Experience collaborating with data governance teams on data ownership, definitions, metadata, lineage, quality standards, and governance processes
• Pharmaceutical or Life Sciences domain experience with understanding of business processes and data requirements
• Comfortable with command-line tools and YAML for configuration management; experience with data governance platforms such as Collibra is advantageous