Enterprise Data Architecture Analyst, Short-Term

Organizational Context

The United Nations Development Programme (UNDP) is a global organization dedicated to eradicating poverty, reducing inequalities, and fostering sustainable development. This role supports the Economics, Sustainable Finance, and Growth department, contributing to UNDP's mission within Moldova.

Job Purpose

The Enterprise Data Architecture Analyst will play a crucial role in enhancing UNDP's data management capabilities. This position is responsible for analyzing, designing, and implementing data architecture solutions that support the organization's strategic objectives. The analyst will ensure data integrity, accessibility, and security, enabling informed decision-making and efficient program delivery across various initiatives. The role contributes to strengthening UNDP's operational effectiveness and its ability to leverage data for impactful development outcomes.

Responsibilities

The Enterprise Data Architecture Analyst will be responsible for developing and maintaining the enterprise data architecture, including data models, standards, and governance frameworks. This includes analyzing business requirements to design appropriate data solutions, ensuring alignment with overall IT strategy. The role involves collaborating with stakeholders to understand data needs and challenges, and translating these into technical specifications. Responsibilities also include evaluating and recommending data management technologies, and contributing to the implementation of data integration and warehousing strategies. The analyst will ensure data quality, consistency, and compliance with relevant policies.

Work Experience

A minimum of 3 years of experience in enterprise data architecture, data modeling, and data management is required. Experience with data governance principles and practices is also necessary.

Skills

Data Architecture, Data Modeling, Data Management, Data Governance, Stakeholder Collaboration, Technical Specifications, IT Strategy, Data Quality, Data Integration.

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