About the position
Role Purpose
The Analytical Engineer is responsible for transforming complex, raw data into structured, governed, and analytics-ready datasets that enable advanced reporting, analytics, and decision-making across the organisation.
This role bridges data engineering and analytics by combining strong data modelling expertise with data transformation and analytical capabilities to support enterprise data products and business outcomes.
Key Responsibilities
- Data Modelling & Design
- Design and implement scalable data models (e.g., dimensional and Data Vault) to support analytical use cases.
- Ensure alignment to enterprise data architecture and modelling standards.
- Data Transformation & Engineering
- Develop and maintain ETL/ELT processes to ingest, cleanse, and transform data from multiple sources into trusted datasets.
- Deliver curated, analytics-ready data layers for consumption by downstream users.
- Analytics Enablement
- Enable business intelligence, reporting, and advanced analytics use cases through high-quality data provisioning.
- Partner with data scientists and analysts to support modelling, insights, and data-driven decision-making.
- Data Quality, Governance & Controls
- Ensure data integrity, lineage, and consistency across datasets.
- Apply governance frameworks and standards to support auditability and regulatory compliance.
- Stakeholder Collaboration
- Engage with business and technical stakeholders to translate requirements into data solutions.
- Support delivery within cross-functional squads aligned to enterprise data products.
Required Skills & Experience
- Strong experience in data modelling (Data Vault, dimensional modelling)
- Proficiency in SQL and Python for data transformation and analysis
- Experience with modern data platforms (e.g., Azure, Databricks, Microsoft Fabric)
- Solid understanding of data warehousing, ETL/ELT, and analytics pipelines
- Familiarity with data governance, quality frameworks, and lineage
- Proven ability to combine engineering discipline with analytical problem-solving
Key Competencies
- Analytical thinking and problem-solving
- Attention to data quality and detail
- Strong stakeholder engagement and communication
- Delivery focus within agile environments
- Governance and compliance awareness
Deliverables / Success Measures
- Delivery of trusted, analytics-ready datasets aligned to business requirements
- Implementation of scalable and reusable data models
- Adherence to enterprise data governance and quality standards
- Enablement of timely and accurate reporting and analytics outcomes
- Contribution to data product delivery within GDA squads
Nice-to-Have
- Experience in banking or financial services data environments
- Exposure to real-time/streaming data processing frameworks
- Understanding of DataOps and CI/CD practices
- Certification in data modelling or cloud platforms
Desired Skills:
- Analytical
- Azure Databricks
- Data
- Data Modeling
- Design
- Engineering
- Extract Transform Load (ETL)
