Head of Data & AI

T
Trade NationFinancial services
Workable locations: England, United Kingdom. Poland. Spain. Germany. FranceFull-Time
Salary not disclosed
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Job Details

Required Skills
SQLSnowflakeData modelingBigQuerydbtRedshift

Requirements

  • Proven leadership experience within Data, Analytics or AI functions.
  • Demonstrable success implementing AI solutions that transformed business workflows and delivered measurable impact.
  • Track record delivering projects from concept through production and adoption.
  • Hands-on expertise in SQL, data modelling and analytics engineering.
  • Experience with dbt or similar version-controlled transformation frameworks.
  • Strong understanding of data warehouse architecture and semantic modelling.
  • Experience with Redshift, Snowflake, BigQuery or similar cloud data platforms.
  • Background in financial services, trading, brokerage or capital markets.
  • Experience leading, coaching and developing analytics teams.
  • Experience with CFD, spread betting or brokerage platforms is desirable.
  • Knowledge of trading systems, back-office financial services data structures, or multi-entity, multi-regulator environments is desirable.
  • Exposure to MiFID II, MiFIR or ASIC reporting frameworks, or AI implementation in regulated financial services, is desirable.

Responsibilities

  • Own and drive the AI strategy from opportunity identification through deployment, adoption and value realisation.
  • Redesign business workflows around AI, focusing on practical outcomes.
  • Build AI capability through training, prompt libraries, templates and a network of AI champions.
  • Measure and report AI adoption, success metrics and lessons learned.
  • Own the business-facing gold layer of the data warehouse, including metrics, definitions and quality standards.
  • Develop and extend the semantic data model for consistent access to business data.
  • Champion data self-service across teams.
  • Establish analytics engineering best practices for testing, version control, documentation and code reviews.
  • Simplify and improve the quality of the data estate.
  • Deliver proactive insights and recommendations to senior leadership.
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