Reporting to the Senior Director, the Head, Enterprise Data Management will be responsible for overseeing the implementation and maintenance of the Foundation’s technical data infrastructure, enabling accurate analytics and cross-functional collaboration. The successful candidate will play a key role in delivering the Foundation’s Enterprise Data strategy and platform as part of a newly established Data and Analytics sub-function. The Head, Enterprise Data Management will work closely with the Enterprise Architecture team within the Technology Value Management and Business Partnering sub-function to define the Foundation’s data architecture.

In this leadership role, you will work closely with the Heads of Data Governance and Processing and Enterprise Data Enablement to design and maintain scalable, efficient data pipelines and storage solutions. The focus will be on ensuring the integrity, availability, and security of the Foundation’s data assets to support the recognition of its 2030 goals.

WAYS YOU CAN CONTRIBUTE

• Data Pipeline and ETL Process Development: Oversee the design, development, and maintenance of systems and pipelines for ingesting, integrating, and analyzing data at scale across the Foundation.
• Data Modeling: Design and implement data models to support system interoperability and BI and analytics requirements, working closely with Data Architects following Data Architecture principles. Ensure efficient and reliable data flows across Foundation platforms, supporting implementation of process automation where appropriate to drive efficiency.
• Data Storage: Lead a team of Data Engineers and Architects to design, develop, and maintain scalable and efficient data storage architectures, including data warehouses and data lakes.
• Data Architecture Framework: Work with the Data and Analytics Senior Director and wider DDIT to define and operationalize a fit-for-purpose Data Architecture framework which is scalable and supports the Foundation’s core objectives.
• Data Architecture Implementation: Oversee a team of Data Architects to implement the Foundation’s Data Architecture, including data integration, metadata management, and data lineage tracking capabilities.
• Solution Architecture: Work with the Enterprise Architecture team to co-create solutions which meet the need of stakeholders across the Foundation, including Enterprise Data Enablement.
• Data Quality Management: Lead Data Quality Management for DDIT and the wider Foundation, working closely with the Head of Data Governance and Processing to conduct regular data audits and assessments. This role will ensure data quality and completeness in collaboration with stakeholders across the Foundation, including Programs and Impact functions.
• Developing the Foundation’s Data Strategy: Collaborate with the Data and Analytics Senior Director and Data Heads to develop and implement the Foundation’s data strategy, in line with the Foundation’s key strategic goals.
• Leadership and Team Development: Provide guidance, coaching, and mentorship to staff of varying experience levels. Foster a collaborative and inclusive environment to support individuals’ professional development and grow the Foundation’s Enterprise Data Management capability.

• Data Pipeline and ETL Process Development: Oversee the design, development, and maintenance of systems and pipelines for ingesting, integrating, and analyzing data at scale across the Foundation.
• Data Modeling: Design and implement data models to support system interoperability and BI and analytics requirements, working closely with Data Architects following Data Architecture principles. Ensure efficient and reliable data flows across Foundation platforms, supporting implementation of process automation where appropriate to drive efficiency.
• Data Storage: Lead a team of Data Engineers and Architects to design, develop, and maintain scalable and efficient data storage architectures, including data warehouses and data lakes.
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• Expertise in SQL and hands-on experience with development in cloud data platforms (e.g., AWS, Azure, Google Cloud) using Python or similar languages.
• Familiarity with modern SDLC practices and agile methodologies.
• Strong understanding of data modelling fundamentals and how to implement these to enable interoperability and more robust analytics.
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• Bachelor’s degree in Computer Science, Information Technology, Data Engineering, or a related field. Master’s degree preferred.
• 8 years of experience in data management or a related role, with experience in the international development, research, or social sectors preferred.
• Minimum of 3 years’ experience in leadership roles, with the ability to build collaborative relationships across the business and support the development of direct reports through mentoring and training.
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