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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