Director / Executive Director - Data Platform and Tools Engineering

Position Overview

We are seeking a seasoned leader to spearhead the engineering, deployment, and advancement of our enterprise data platform to ensure robust scalability, reliability, optimal performance, and operational excellence across diverse data workloads. This role will oversee cloud-native infrastructure, data ingestion pipelines, transformation frameworks, and analytical platforms spanning multiple regions.

Core Responsibilities

• Guide the design, implementation, and ongoing refinement of enterprise data platform infrastructure that supports all data workload types with a focus on scalability and operational quality.
• Manage cloud-native solutions for processing structured, semi-structured, and unstructured data across various jurisdictions.
• Create and maintain flexible data ingestion frameworks accommodating batch, streaming, real-time, event-based, API, and file integrations.
• Develop reusable ingestion tools including accelerators, connectors, orchestration mechanisms, and metadata-driven onboarding solutions to enhance consistency and reduce effort.
• Lead the engineering and evolution of scalable data transformation frameworks with reusable patterns, standardized code practices, robust testing, and deployment automation.
• Oversee enterprise business intelligence and visualization tools ensuring secure, scalable, and governed access to analytics and reporting features.
• Establish and maintain analytics workbench environments for analysts, data scientists, and AI engineers, including notebooks, collaboration tools, feature engineering setups, and experimentation platforms.
• Drive development of enterprise capabilities integrating large language models (LLMs) such as connectivity services, prompt orchestration, retrieval, vector databases, and agent enablement.
• Build reusable AI services ensuring compliant and secure access to internal and external foundational models adhering to security and regulatory policies.
• Formulate standards for Infrastructure-as-Code, environment provisioning, automation, release management, DevSecOps, and continuous delivery pipelines.
• Implement platform observability including monitoring, logging, telemetry, operational dashboards, and alerting.
• Conduct capacity planning, optimize workloads, manage resources, and tune performance within data and AI environments.
• Lead cost management strategies covering cloud financial oversight, workload efficiency, storage lifecycle, compute usage, and vendor license optimization.
• Enforce data security controls encompassing encryption, tokenization, masking, secrets & key management, access control models, and data protection mechanisms.
• Collaborate with cybersecurity, infrastructure, and risk teams ensuring compliance with security, regulatory, and resilience standards.
• Partner with Data Design & Models teams to align platform capabilities with metadata standards, semantic frameworks, data products, and emerging business needs.
• Work closely with Data Engineering & Delivery teams to offer reusable frameworks, tools, and platform components accelerating business solution delivery.
• Manage strategic vendor relationships and technology investments in the data and analytics ecosystem to maximize value and efficiency.
• Build and lead diverse, high-performing teams across Asia Pacific and global locations including platform engineers, cloud and DevOps engineers, platform specialists, and engineering leads.
• Continuously evaluate emerging tech and engineering best practices to enhance developer productivity, operational performance, reliability, and business impact.

Required Qualifications and Expertise

• At least a decade of leadership experience in enterprise data platform engineering, cloud platform engineering, or managing large technology teams within complex financial services settings.
• Demonstrated ability to develop and operate enterprise-scale data platforms that support analytics, regulatory reporting, and sophisticated data workloads.
• Expert knowledge of contemporary data platform technologies including Databricks, Snowflake, Kafka, Spark, Delta Lake, Airflow, Kubernetes, OpenShift, and cloud-native services.
• Proven experience designing and implementing ingestion and transformation frameworks, event-driven architectures, streaming platforms, API integrations, and distributed processing environments.
• Competence in building analytics workbenches and data science platforms facilitating advanced analytics, machine learning, and artificial intelligence development.
• Strong understanding of AI integration patterns including large language model frameworks, retrieval systems, vector databases, model access services, and AI engineering methodologies.
• Hands-on experience with Infrastructure-as-Code, CI/CD pipelines, DevSecOps processes, platform observability, and automated operational controls.
• Expertise in cloud financial management, including optimizing platform costs, workload management, and scaling large platforms.
• In-depth knowledge of enterprise security including identity and access management, RBAC, ABAC, encryption, tokenization, secrets management, and data protection technologies.
• Proven leadership of geographically dispersed engineering teams, platform modernization projects, and strategic vendor partnerships.
• Experience managing extensive technology budgets and optimizing delivery and operational expenses in multiple jurisdictions.
• Excellent stakeholder engagement, communication, and persuasive skills to foster organization-wide platform adoption and engineering improvements.
• Prior banking and financial services experience supporting regulatory, risk, finance, and operational requirements across multiple regions is advantageous.