Director/Executive Director, Data Platform & Tools Engineering
On-siteTokyo, Tokyo, Japan
Job Summary
Lead the engineering, implementation, and continuous evolution of the enterprise data platform, ensuring scalability, resilience, and operational excellence across all data workloads. Develop and operate cloud-native infrastructure supporting structured, semi-structured, and unstructured data processing while establishing reusable ingestion accelerators and metadata-driven onboarding frameworks. Own the engineering of enterprise transformation frameworks, business intelligence platforms, and analytics workbenches for data scientists and AI engineers. Lead the development of LLM integration capabilities, including model connectivity services, prompt orchestration, and vector database integrations, while implementing Infrastructure-as-Code, DevSecOps, and platform observability. Manage strategic vendor relationships, platform capacity planning, and cost optimization initiatives across multiple jurisdictions. Build and lead high-performing teams of platform and cloud engineers across Asia Pacific and the Global Capability Center, collaborating with Cyber Security, Data Design, and Delivery teams to ensure compliance and accelerate business solution delivery.
Required Qualifications
- Minimum 10 years' experience leading enterprise data platform engineering, cloud platform engineering, or large-scale technology organizations within complex financial services environments
- Proven experience building and operating enterprise-scale data platforms supporting analytics, regulatory reporting, and advanced data workloads
- Deep expertise in modern data platform technologies including Databricks, Snowflake, Kafka, Spark, Delta Lake, Airflow, Kubernetes, OpenShift, and cloud-native data services
- Strong experience designing and implementing enterprise ingestion frameworks, transformation frameworks, event-driven architectures, streaming platforms, API integration frameworks, and distributed processing environments
- Experience engineering enterprise analytics workbenches and data science platforms supporting advanced analytics, machine learning, and AI development
- Strong knowledge of modern AI integration patterns including LLM integration frameworks, retrieval architectures, vector databases, model access services, and AI engineering practices
- Experience implementing Infrastructure-as-Code, CI/CD pipelines, DevSecOps practices, platform observability, and automated operational controls
- Strong expertise in cloud financial management, platform cost optimization, workload management, and large-scale platform operations
- Deep understanding of enterprise security architecture including IAM, RBAC, ABAC, encryption, tokenization, secrets management, and data protection technologies
- Proven experience leading geographically distributed engineering teams, platform transformation initiatives, and strategic technology vendor partnerships
- Experience managing sizable technology budgets and optimizing both delivery and operational costs across multiple jurisdictions
- Strong stakeholder management, communication, and influencing skills with the ability to drive enterprise-wide platform adoption and engineering excellence
Desired Qualifications
- Banking and financial services experience supporting multi-jurisdiction regulatory, risk, finance, and operational environments preferred
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