Data Quality Analyst

About the role

About Imagine Worldwide All children have immense potential, but hundreds of millions don’t have access to the learning they need. Imagine Worldwide believes that every child should be empowered with the basic right to literacy and numeracy. We provide an innovative education technology solution and implementation model to the global literacy/numeracy learning crisis using the onebillion application and various toolkits and systems to support implementation. Our model is massively scalable, evidence-based, and can deliver foundational learning to millions of the most marginalized children. Imagine Worldwide partners with governments, organizations, and communities to provide child-directed, tablet-based learning that is accessible, effective, and affordable. We are incorporated in California (United States) as a nonprofit organization, but operate in Sub-Saharan Africa through locally-registered entities in Malawi, Sierra Leone, and Tanzania. Learn more on our website. Role Overview The Data Quality Analyst focuses on data quality across Imagine’s data ecosystem. The role proactively monitors data from devices, programme systems and field sources, builds and improves the checks that catch problems early, and investigates issues raised across the organisation. Where an issue requires deeper analysis, reporting changes or engineering work, the role provides its findings and works with the relevant team member to resolve it.  Imagine’s data covers learning activity from tablets in more than 1,500 schools, along with programme, operational and field data. Devices sync intermittently and sources don’t always agree, so checking data against what is happening in schools and in the field is central to the work. The role reports to the Director of Analytics and works closely with the Data Scientist, who provides methodological support.  It suits an analyst who enjoys tracing a problem back to its source and wants to keep developing in a small team. As they build context on Imagine’s data, the role takes on more ownership of the team’s data quality reporting and standards. Key Responsibilities The Data Analyst’s responsibilities fall into four pillars: data quality monitoring and improvement, data issue investigation, communicating findings, and analytical practice. Data Quality Monitoring and Improvement  The role takes a proactive approach to data quality, identifying risks and gaps before they affect reporting or decision-making.  • Monitor the completeness, consistency and plausibility of data across Imagine’s sources, and identify issues independently. • Design and implement data quality checks, and recommend where further checks or controls are needed across pipelines and source systems. • Develop tooling and automated monitoring that make data quality issues visible, working with the Analytics Engineer on implementation within the platform. • Reconcile figures across related sources and investigate discrepancies. • Contribute to the team’s data quality reporting, rules and standards. Data Issue Investigation  The role is the Analytics Team’s first point of investigation when data issues are identified, whether through monitoring or raised by colleagues.  • Investigate data issues and trace them to their root cause across source systems, pipelines and data models. • Work with the Analytics Engineer, MEAL and country teams to resolve issues at source and confirm their resolution. • Handle assigned data quality and data export requests from the Analytics Team’s request process. • Document findings and hand over issues that require deeper analysis, reporting changes or engineering work to the relevant team member. • Support the team’s data quality incident process by providing the evidence needed for decisions. Communicating Findings • Write concise summaries of data issues and investigations, covering the cause, the impact and the recommended action. • Report on the state of data quality to the Analytics Tea