Director, Data and Information Systems

Overview

The Director will provide strategic and technical leadership for projects in Uganda . They will supervise specialist staff in information systems, M&E and data analytics; translate programmatic requirements into clear system and analytical requirements; and provide sufficient technical oversight to ensure that the resulting architecture and tools are robust, practical and fit for purpose.

 Responsibilities

Data Architecture and Dashboard for Performance Management (40% LOE)

• Lead the design and operationalization of an integrated data and information architecture supporting the activity’s risk assessment, milestone verification, and performance-management functions.
• Lead the functional design of an integrated performance management dashboard for Government of Uganda, U.S. Government and project users, providing accessible and decision-relevant information on entity risk profiles, assessment and verification progress, findings, data quality, risk-mitigation actions and performance.
• Translate programmatic and technical requirements into clear system requirements, data structures, workflows, business rules and analytical specifications, working with the Information Systems Manager, MEL Manager and other technical specialists to turn these requirements into practical tools and systems.
• Lead the activity’s approach to accessing and using data from relevant Government of Uganda systems—including IFMIS, HMIS/DHIS2, human-resource information systems and other financial and administrative systems—determining what information is required, how it should be structured and linked, and how it can be reliably incorporated into the activity’s data environment.
• Establish appropriate standards and processes for data governance, documentation, access, security, interoperability and quality, ensuring that the activity maintains reliable and appropriately controlled information while working across multiple government and project data sources.
• Lead the development of verification template/tools for secondary and primary verification data.
• Develop verification schedule.
• Ensure that all relevant entities receive automated notifications, acknowledge receipt, and prepare the required source documents in advance of onsite verification.
• Lead the planning and execution of periodic data quality assessments.

Data Analytics (30% LOE)

• Work with technical leads to translate risk assessment, verification and DQA approaches into practical indicators, analytical rules, risk flags and other decision-support tools.
• Lead the use and triangulation of data from different sources to identify emerging risks, unusual patterns, discrepancies and areas requiring further assessment or verification.
• Identify opportunities to standardize and automate routine analysis and checks, making assessment and verification more efficient and better targeted over time.