Strong experience in data architecture and data modelling, including canonical and dimensional modelling across complex business domains
Proven ability to understand complex data landscapes and translate business concepts, source structures, and requirements into clear, coherent data models that engineering teams can build against
Experience analysing and profiling data across multiple sources, including complex or poorly documented legacy environments, to establish structure, quality, relationships, meaning, and usage
Strong understanding of data entities, relationships, grain, semantics, business measures, source-to-target mapping, and data lineage
Strong SQL skills, with the ability to explore and profile source data as part of discovery and modelling activities
Experience defining source-to-target mappings and identifying gaps, inconsistencies, and data quality issues across diverse data sources
Experience translating business and technical stakeholder requirements into clear data definitions, models, mappings, and architectural decisions
Strong stakeholder engagement skills, with the ability to move confidently between conversations with business users, domain experts, architects, and engineering teams
Experience working closely with data engineering teams to ensure models and mappings can be translated into practical, implementable solutions
Experience documenting complex data models, schemas, mappings, lineage, assumptions, and architectural decisions using appropriate data modelling and documentation tools
Experience working with large-scale analytics or enterprise data platforms and an understanding of modern lakehouse architectures
Exposure to cloud-based data ecosystems, ideally AWS and/or Snowflake; familiarity with AWS data services such as S3 or Glue would be advantageous
Experience working with media, audience, ad-tech, or content analytics data would be advantageous
Excellent communication and documentation skills, with the ability to bring structure and clarity to ambiguous and complex data problems
Intellectual curiosity and a proactive approach to understanding how data is created, used, and interpreted across a business
Experience with large-scale analytics platforms
Experience with media, audience, or similarly complex behavioural data would be a plus