Description
- Lead the Client Technology Data & Analytics function to turn client data into scalable, trusted data products and actionable insight across the bank.
The role owns the strategy, architecture and operation of data platforms aligned to the Client Technology domains:
- Client Relationship Management
- Client Onboarding (corporates and individuals)
- Client Content & Communications (statements, SMS, email, etc.)
- Client Data Management (core client data storage and management)
- Client Technology is a central division, so these platforms supply data products and insights to multiple business units and functions across the bank.
The Head of Data & Analytics is accountable for:
- Defining and executing the data strategy for Client Technology
- Building and scaling an internal Data & Analytics capability (Data Engineers and Data Analysts)
- Ensuring client data is well-governed, high quality and reusable
- Delivering data products and insights that enable better client experiences, better onboarding and servicing, and profitable growth, while managing risk and complying with governance and regulatory standards.
Key outcomes
- A clear, prioritised Client Data & Analytics roadmap for data domain platforms, aligned with the Client Technology strategies.
- High-quality, well-governed client data products that are widely reused across the bank (single sources of truth for client, onboarding and communication data).
- Robust Azure-based data platforms for ingestion, transformation and curation, with clear SLAs for availability, performance and data freshness.
- Embedded analytics and reporting that help business and product teams improve client acquisition, onboarding, engagement, retention and risk decisions.
- A small but high-performing Data & Analytics team (Data Engineers and Data Analysts) with a clear growth path and operating model as demand scales.
- Strong adoption of standard patterns and reusable components, reducing duplication and one-off builds across the client domains.
Key responsibilities
Strategy & governance
- Act as data owner/steward for client, onboarding, communications and related client data domains within Client Technology.
- Define and enforce data standards, reusable patterns and best practices across the four domain data platforms.
- Partner with group Data Governance, Risk, Compliance and Information Security to ensure client data solutions meet governance, privacy, security and regulatory requirements.
- Define and track data quality and governance metrics (e.g. completeness, accuracy, timeliness, lineage) for client data.
Architecture, platforms & data products
- Own the end-to-end architecture of the four client data platforms on Microsoft Azure, from ingestion through to curated data products and interfaces.
- Ensure scalable, secure and well-designed data ingestion, transformation and curation pipelines that support both operational and analytical use cases.
- Translate business problems from Client Technology domains (CRM, onboarding, communications, client data management) into data product and data platform requirements.
- Define and oversee data models and domain boundaries across the four platforms to support a consistent, reusable client data foundation.
- Provide technical leadership and design authority: review solution designs, sign off patterns, and step in hands-on where needed to unblock complex delivery.
Analytics, reporting & insight
- Lead the analytics and reporting agenda for Client Technology, ensuring that data products surface clear, actionable insight for business and product stakeholders.
- Work with Data Analysts and Product/Business teams to define key metrics and dashboards across client lifecycle, onboarding journeys, communications performance and data quality.
- Enable and support the use of predictive modelling, NLP and ML on client data where appropriate (e.g. segmentation, propensity, communications optimisation), in collaboration with other Data teams where relevant.
Leadership, team & operating model
- Lead a growing Data & Analytics team (Data Engineers, Data Analysts and Data Scientist), setting the technical direction, ways of working and priorities.
- Define the operating model for the team: engagement model with the four Technical Domains and across the Organization, allocation of capacity, backlog management and standards for delivery.
- Coach and mentor team members, drive skills development (particularly on Azure data services and modern data engineering practices) and build a pipeline of talent as the function grows.
- Foster a culture of collaboration, ownership, autonomy and inclusion, with high standards for delivery and engineering quality.
Stakeholder management & collaboration
- Build strong partnerships with Domain Leads in Client Technology (CRM, Onboarding, Content & Comms, Client Data Management) and with Product Owners, Business, Risk and Operations.
- Communicate complex data concepts and trade-offs in simple, business-relevant language to both technical and non-technical stakeholders.
- Coordinate with the broader Cloud & Engineering practice to share patterns, leverage common tooling and avoid duplication.
- As a member of the Client Technology Manco, contribute to strategic decisions, planning and prioritisation from a data perspective.
Knowledge, skills & experience
Technical & platform skills
- Deep experience with Microsoft Azure data services (e.g. data storage, data processing and orchestration services used in your stack) for ingestion, transformation and curation.
- Experience with Azure DevOps, GitHub or similar CI/CD and source control platforms.
- Proficiency in C#, Python and T-SQL.
- Experience with Platform as a Service (PaaS) and Infrastructure as Code, scripting and automation in Azure.
- Strong data modelling and design skills (e.g. dimensional models, data vault, domain-driven models) for operational and analytical needs.
- Familiarity with data virtualisation, data warehousing/lakehouse concepts and common reporting/BI tools.
Leadership & communication
- Demonstrable technical leadership: setting standards, reviewing designs, guiding engineers and analysts.
- Strong stakeholder management across multiple domains and business areas.
- Excellent written and verbal communication skills; comfortable presenting to Manco/Exco-level as well as deep-dive technical sessions.
Experience & qualifications
- 10+ years overall experience in data / analytics / software engineering, with at least 5 years in data leadership roles (to be tuned as required).
- Experience delivering data platforms and data products at scale, ideally in financial services / banking.
- Degree in Computer Science, Engineering, Mathematics, Statistics, Information Systems or related field; postgraduate degree advantageous.
- Relevant Azure certifications and/or data management certifications beneficial.
Gmail
Yahoomail