Data Architect
Indexed description
Key Responsibilities
Data Modelling & Structure
- Define and maintain canonical data models across domains
- Design scalable data structures to support analytics and reporting
- Ensure consistent definitions of key business entities and metrics
- Data Architecture & Integration
- Design end-to-end data architecture (ingestion → transformation → consumption layers
- Define integration patterns for internal systems and external APIs
- Support both batch and real-time data flows where required
- Ensure alignment between operational systems and analytical data structures
- Define and enforce data standards, naming conventions, and modelling practices
- Work with the Data & Insights Manager to establish data ownership and governance
- Ensure consistency and reusability of datasets across teams
- Provide architectural guidance to Data Engineers
- Review and approve data design decisions
- Ensure scalability, performance, and maintainability of data solutions
- Define frameworks for data quality, validation, and reconciliation
- Ensure alignment of data definitions across business domains
- Support resolution of data discrepancies
- 5–10+ years experience in data architecture, data modelling, or senior data engineering roles
- Strong expertise in data modelling (e.g. dimensional modelling, normalisation, semantic layers)
- Proven experience designing scalable data architectures (warehouse, lake, or lakehouse)
- Strong understanding of data pipelines (ETL/ELT) and transformation patterns
- Experience working with API-driven and/or event-based systems
- Ability to define and enforce data standards and governance practices
- Experience working closely with engineering and analytics teams
- Strong problem-solving skills with attention to data consistency and correctness
- Experience in iGaming, fintech, or high-volume transactional systems
- Experience modelling event-based data (e.g. transactions, sessions, gameplay flows)
- Familiarity with modern data stack tools (e.g. Snowflake, BigQuery, dbt, Kafka)
- Experience with real-time or streaming data architectures
- Exposure to regulatory or compliance-driven data environments
- Experience supporting AI/ML data readiness
- Success Metrics
- Consistent and reusable data models across domains
- Reduction in data duplication and conflicting definitions
- Improved data quality and trust across the organisation
- Scalable architecture supporting current and future use cases
- Experience a dynamic and team-orientated work environment.
- Opportunities for personal growth and learning
- An open, inclusive and supportive team where you will be valued, and your suggestions will be welcome.
- 26 days paid holiday per year. This is in addition to local public holidays.
- Competitive salary
- Hybrid Working
- Risk Benefits such as pension, Life Assurance (4x annual salary), Private Medical Insurance
- Team Building Opportunities
- Flexible core hours between 10am – 4pm
- Receive support whenever you need it with our Employee Assistance Program, available 24/7.
- Local discounts and more.
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