Tianjin, CN
Live, first seen by us 24 days agoDefine the multi-year Post Trade Data strategy, target architecture and investment roadmap
Converge fragmented data stores and pipelines into reusable strategic services
Establish governed data products with ownership, metadata, lineage and controls
Build governed data foundations for analytics and AI with human oversight
Ensure scalable, observable and recoverable data services and strengthen controls
Define and execute the multi-year Post Trade Data strategy, target architecture and investment roadmap
Converge fragmented data stores and pipelines toward reusable strategic services
Establish authoritative data products and controls covering ownership, metadata, lineage, critical data elements
Build governed data foundations for analytics and AI
Ensure scalable, observable and recoverable data services
15+ years of Financial Markets technology experience
with significant leadership responsibility across enterprise data platforms
Post Trade Data Architecture and Engineering
Data Governance, Quality and Lineage
Technology Strategy, Innovation and AI Enablement
From the employer’s posting.
Our strategy, which combines cross-border capabilities and leading wealth management expertise, helps us deliver our purpose - to drive commerce and prosperity through our unique diversity.
In the employer’s words · Read in context
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New Data Leadership postings at the employers we follow are about the same over the last 6 weeks compared with the 6 before.
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We file this job under Data Leadership, by the work the posting describes.
Data leaders run data teams or design how a company's data fits together. Managers hire, set priorities and answer for whether the data work pays off; architects choose the systems and the shape of the data.
Expect years of hands-on data work, experience leading people or projects, and the ability to explain tradeoffs to executives.
Unlike a senior engineer or analyst, most of a data leader's week goes to people, planning and decisions rather than building.
The government has no code for data leaders, so these figures are for the closest group, computer and information systems managers, which includes data processing and data operations managers.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 11-3021.
Lead the global Post Trade Data technology organisation, accountable for the strategic data capabilities that underpin post trade services and processes across Markets.
Own the strategy, target architecture and investment roadmap for the Post Trade Data technology portfolio, including DQSL, SSDR, DQMA, DMR/Rosetta, FM-MIS and related services, establishing a unified and scalable data foundation for Post Trade Services.
• Establish governed, discoverable and AI-ready data products with clear ownership, metadata, lineage, entitlements, privacy and control standards, enabling reliable reuse by Operations, Reporting, Regulatory and client-facing capabilities.
• Drive platform convergence, application simplification, intelligent data-quality management, observability and automation to improve timeliness, consistency, resilience and cost efficiency.
• Act as the senior technology partner for Markets Product, Markets COO, Operations, Data Office, Risk, Compliance, Architecture and Markets Technology leadership on post-trade data strategy, investment and transformation.
The role holder leads others and is accountable for strategic direction, delivery outcomes, financial and technology risk management, stakeholder alignment and talent development across the global Post Trade Data technology organisation.
• Strategy and transformation: Define and execute the multi-year Post Trade Data strategy, target architecture and investment roadmap, aligned to Markets Technology, Post Trade Services, enterprise data standards and regulatory priorities.
• End-to-end capability ownership: Own the Post Trade Data application portfolio, including DQSL, SSDR, DQMA, DMR/Rosetta and related data services, with accountability for enterprise data ingestion, enrichment, distribution, quality, metadata, lineage, controls and governed data consumption across Post Trade Services. Maintain clear ownership of platform strategy, service performance, resilience, controls and lifecycle management.
• Trusted and governed data: Establish authoritative data products and controls covering ownership, metadata, lineage, critical data elements, reconciliation, entitlements, security, privacy, retention and quality monitoring.
• Architecture and modernisation: Converge fragmented data stores and pipelines toward reusable strategic services, including unified processing, data-quality and analytics layers, while reducing duplication, obsolescence and technical debt for the Post Trade Data ecosystem, including DQSL, SSDR, DQMA, DMR/Rosetta and related data services.
• AI-ready foundations and innovation: Build governed data foundations for analytics and AI; apply intelligent data-quality controls, anomaly detection, automated lineage and AI-enabled engineering with appropriate security, model-risk and human oversight.
• Resilience, controls and regulatory readiness: Ensure scalable, observable and recoverable data services; strengthen preventive and detective controls, audit evidence, cyber remediation and readiness for regulatory and country change.
• Portfolio and financial governance: Accountable for portfolio investment decisions, delivery of strategic business cases, technology cost efficiency, workforce strategy, vendor management, run-and-change spend and realisation of platform simplification and productivity benefits.
• Stakeholder and people leadership: Partner with Product, Operations, Reporting, Regulatory Technology, Data Office, Risk, Compliance, Architecture and Cyber Security; lead a global team with clear accountability, succession and engineering excellence.
People and Talent
• Set direction and drive high performance by translating strategy into clear direction, aligning individual goals to team outcomes and providing regular, constructive feedback.
• Develop talent and capability through coaching and career conversations that build critical skills, stretch potential and prepare individuals for future opportunities.
• Lead by example by role-modelling the Bank’s valued behaviours, upholding strong risk and conduct standards, exercising sound judgment, and creating an inclusive team culture that supports wellbeing, values diverse perspectives, and drives accountability.
Must-have Skills
• Post Trade Data Architecture and Engineering
• Data Governance, Quality and Lineage
• Technology Strategy, Innovation and AI Enablement
Other Skills
• Technology Platform and Engineering Leadership
• Data Risk, Controls and Regulatory Readiness
• People Leadership and Team Culture
• Strategic Stakeholder and Portfolio Management
This role is energised by turning complex, fragmented post-trade data into trusted, reusable and strategically valuable enterprise capabilities.
• Building high-performing global data engineering teams and a culture where data ownership, quality, resilience and control are embedded by design.
• Delivering measurable improvements in data timeliness, consistency, discoverability, reuse, operational resilience and time-to-insight.
• Creating governed and AI-ready foundations that accelerate reporting, analytics, automation and decision support across Post Trade Services.
Key Experiences
• Demonstrable experience leading enterprise-scale data platforms, streaming and processing capabilities, data-quality controls, governance and analytics enablement in production environments.
• Strong technical credibility to challenge data architecture, integration, cloud, security, lineage and control decisions and translate them into business and operational outcomes.
• 15+ years of Financial Markets technology experience with significant leadership responsibility across enterprise data platforms. Demonstrated experience delivering real-time ingestion and processing, data-quality management, governance, lineage, distribution, analytics or AI-ready data foundations, platform modernisation and resilience.
• Proven ability to lead global teams, manage material investment and vendor portfolios, and deliver resilient, governed and scalable data outcomes.
Certifications / Qualifications
• Bachelor's degree required; Master's degree or equivalent postgraduate qualification preferred.
• Relevant certifications in Data Management, Data Architecture, Cloud Engineering, AI/ML, Data Governance or Enterprise Architecture are advantageous.
Languages
• English required. Additional regional language capability is beneficial for global team and stakeholder engagement.
We're a global bank connecting clients to our differentiated network, offering growth opportunities in the world's most dynamic markets. Our strategy, which combines cross-border capabilities and leading wealth management expertise, helps us deliver our purpose - to drive commerce and prosperity through our unique diversity.
Over our 170-year history, and across a unique geographical footprint connecting Asia, Africa and the Middle East to each other and the world, we've built a bank like no other, with diverse capabilities and partnerships that set us apart.
Visit our careers website to learn more about us: www.sc.com/careers.
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Tianjin, CN
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