Principal accountabilities and responsibilities:
- Lead product delivery of data foundations for Operational Resilience, providing a governed, reusable data layer that underpins how the bank measures resilience, maps service dependencies and tests scenario assumptions across Procurement and Real Estate Services
- Own the roadmap and backlog for one or more data products (e.g. Procurement spend, supplier performance, real estate portfolio performance, operational KPIs), aligned to business outcomes and strategic data model
- Translate stakeholder needs into clear product requirements i.e. Problem statement, user journey, use cases, acceptance criteria, value hypotheses, and measurable outcomes (OKRs, KPIs)
- Drive end-to-end delivery through the full data product lifecycle, ensuring reusability and consistent consumer experience
- Partner with Data Engineers, Analysts, Architects, and Data Governance to define data models, data contracts, metadata, lineage, quality rules, retention and access controls in line with HSBC standards and policies
- Publish Data Products to the Data Fabric with appropriate documentation, certification, and consumption guidance (e.g. Semantic definitions, metric logic, SLAs)
- Prioritise delivery using Agile practices (refinement, sprint planning, demos, retrospectives), managing dependencies and removing blockers across multiple teams
- Oversee data quality assessment and continuous improvement (completeness, accuracy, timeliness, consistency), including monitoring and incident resolution where required
- Drive adoption & stakeholder engagement, communications, training materials, and enablement for consumers (MI / reporting teams, analysts, operational users)
Skills/experience required:
- Strong understanding of Operational Resilience concepts and hands-on experience with relevant data e.g.
service / impact tolerances, asset dependency incidents / outages, DR / BCP test evidence, concentration indicators
- Conceptual understanding of Procurement / Real Estate and associated data domains preferred
- Demonstrable experience in a data-related role (data product, analytics, data operations, data engineering, MI delivery) with ownership of outcomes
- Strong capability in requirement gathering & analysis, stakeholder engagement, and use case management, able to move from ambiguity to a prioritised plan
- Working knowledge of data architecture, data management, data governance concepts
- Experience building or managing data assets aligned to business outcomes and strategic data models (e.g. Curated datasets, KPIs, semantic models, reports)
- Understanding of data architecture and data modelling (conceptual / logical), and how design decisions impact downstream consumption and scalability
- Practical experience with data quality assessment, uncovering inconsistencies across systems, and driving remediation with accountable owners
Familiarity with modern data platform patterns (e.g. Metadata-driven discovery) and operating models for reusable data products
- Strong product delivery skills (backlog management, prioritisation, MVP definition, release planning), experience with JIRA and Confluence
- Ability to communicate through clear narratives and practical value cases, comfortable presenting solutions to technical and non-technical stakeholders
- Technical literacy, confidence working with SQL, python, analytics tooling, experience with cloud data platforms
(GCP, Big Query)