Qualifications
• Relevant degree or equivalent experience.
• Azure DP-203 (or equivalent)
• Certification in Data Governance and Stewardship Professional (DGSP) or similar (desirable).
• Evidence of business experience or formal business qualifications (desirable).
Experience
• Proven experience in technical leadership roles (e.g., Lead Developer, Senior Data Engineer, Head of Data) within regulated environments.
Knowledge of the following is required:
o Modern Data platform concepts; Data Lake, Lakehouse, Data Warehouse, Data Vault
o Azure Data Technologies; Azure Data Lake Storage, Azure Data Factory, Azure Databricks, MS Fabric
o ETL / ELT processes and designing, building and testing data pipelines
o Building data transformations using python / pyspark
o Azure Cloud Version control and CI/CD tools, specifically Azure DevOps Service
o Analytics and MI products including MS Power BI
o Data catalog & governance using MS Purview
Knowledge of the following would be desirable:
o Microsoft server-based data products (SQL Server, Analysis Services, Integration Services and Reporting Services)
o Enterprise Architecture tools (e.g. LeanIX, Ardoq), Frameworks (TOGAF) and core artefacts (Capability Models, Technical Reference Models, Data Flow Diagrams
o Experience developing and implementing technology roadmaps and target state architectures.
o Experience integrating bespoke software, commercial off-the-shelf packages and third-party services.
o Demonstrable experience of migrating on-premises workloads to cloud-native services
o Excellent analytical, problem-solving and communication skills.
o Strong stakeholder management and influencing abilities at all levels.
o Ability to work efficiently under pressure and lead teams in adverse situations.
o Commitment to continuous learning and keeping skills current.
Skills
• Must be able to provide effective leadership within the data space, particularly when navigating ambiguity.
• Must be comfortable making decisions and able to effectively execute the plan in a fast-paced environment.
• Excellent verbal and written communication with a proven track record of stakeholder engagement and influencing both business and technical stakeholders
• Ability to communicate between the technical and non-technical - interpreting the needs of technical and business stakeholders, communicating how activities meet strategic goals and client needs.
• Ability to analyse data to drive efficiency and optimisation, design processes and tools to monitor production systems and data accuracy.
• Ability to produce, compare, and align different data models across multiple subject areas, reverse-engineering data models from a live system where required.
• Excellent analytical and numerical skills are essential, enabling easy interpretation and analysis of large volumes of data
• Excellent problem solving and data modelling skills (logical, physical, semantic and integration models)
Other relevant information
• Experience of wealth management (including operational knowledge) would be advantageous
• Prior experience working in Financial Services preferred, thorough understanding of data security, data privacy, GDPR required
• Certification in TOGAF or equivalent structured architecture framework (desirable).