Digital Program Specialist – Data Analytics (Base in Beijing

Digital Program Specialist – Data Analytics The Asian Infrastructure Investment Bank (AIIB) is a multilateral development bank whose mission is financing Infrastructure for Tomorrow in Asia and beyond – infrastructure with sustainability at its core. We began operations in Beijing in 2016 and have since grown to 111 approved members worldwide. We are capitalized at USD
100 billion and AAA-rated by the major international credit rating agencies. Collaborating with partners, AIIB meets clients’ needs by unlocking new capital and investing in infrastructure that is green, technology-enabled, and promotes regional connectivity.
The Information Technology Department (ITD) provides technical services in the areas of digital services, IT-related procurement, cybersecurity, IT risk and resilience, data management, digital learning, and digital transformation, ensuring their overall alignment with the Bank’s needs and priorities. The team oversees the development and refinement of the IT strategy as well as the effective management of technology resources and the provision of technical support across Bank operations.

These efforts are critical to fostering a digital and data-driven culture within the Bank aligned with its Corporate Strategy, promoting the innovation of digital infrastructures, and ensuring the smooth operation and security of daily functions.
The Digital Program Specialist – Data Analytics will be responsible for bridging business functions and data engineering teams to enable consistent, reliable, and decision-ready data across the Bank. The role will focus on translating business requirements into data logic, aligning KPI definitions and reporting standards across departments, and ensuring data consistency across systems and platforms. It will supports enterprise data initiatives, including management and Board-level reporting, while ensuring that underlying data structures and logic are robust, aligned, and scalable.

Responsibilities:

• Translate business requirements into data definitions, KPI logic, and technical specifications for implementation by data engineering teams.
• Work closely with business stakeholders to clarify data needs, interpret business processes, and ensure accurate representation in data models and systems.
• Define and document business data logic, ensuring traceability between business requirements, data transformations, and reporting outputs.
• Independently coordinate with core departments to align on KPI definitions, reporting logic, and data usage.
• Resolve cross-functional data inconsistencies and ensure alignment across financial, risk, operational, and portfolio domains.
• Act as a central coordination point for data-related topics across business and technical teams.
• Work closely with the data engineering and platform teams to support data model design, data pipelines, and system integration.
• Translate business logic into implementable data transformations, and validate outputs against business expectations.
• Lead and coordinate UAT activities, data validation, and issue resolution across system changes and releases.
• Support data transitions, and ensure continuity and consistency across system upgrades and enhancements.
• Ensure alignment of data definitions, KPI logic, and reporting standards across systems, dashboards, and departments.
• Support the implementation of data governance practices, including controlled logic changes, documentation, and traceability.
• Identify and address gaps in data definitions, data usage, and governance processes.
• Conduct root cause analysis on complex data issues across systems and reporting layers.
• Drive improvements in data processes, data flows, and reporting workflows to enhance consistency and efficiency.
• Identify opportunities to optimize data solutions, improve automation, and enhance scalability of data products.
• Support management and reporting, such as through managing executive-level dashboards, ensuring data accuracy and consistency.
• Provide insights and interpretation to support decision-making where required.
• Ensure that reporting outputs are aligned with underlying data logic, governance standards, and business definitions.

Requirements:…