Head of Data and Analytics Client Tech (12823) at Investec

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.