Data Automation Manager

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The Position

The Data Automation Manager leads the Data Automation Team and owns the technical side of managing Prosper Global’s portfolio-wide data ecosystem, integrating partner and program data, enabling analysis and visualization, and demonstrating impact across the entire portfolio.

The team ensures that Prosper Global can effectively collect, process, integrate, analyze and use data from both Prosper Global and partner systems to support evidence-based decision-making, organizational learning, accountability, donor reporting and external communication. Through data automation, analytics and visualization, the team enables staff and partners to access timely, reliable information that demonstrates results and impact at project, program and portfolio levels. The Data Automation Manager operates within Prosper Global Ukraine’s Technical Support, Evidence and Program Quality (TEQ) Department, which provides technical leadership and quality assurance across the organization’s portfolio. The TEQ Department brings together Monitoring, Evaluation and Learning (MEL) teams across the portfolio, the Community Accountability and Reporting Mechanism (CARM) team, the Social Inclusion and Protection Mainstreaming team, and the Data Automation Team. Together, these functions ensure that Prosper Global programs are high quality, accountable to participants and stakeholders, and continuously informed by evidence, learning, and participant feedback.

The Data Automation Manager leads a team of technical specialists, setting priorities, monitoring progress, and fostering collaboration across internal units and partner organizations. They are responsible for guiding the design and continuous improvement of Azure-based data architecture, including pipelines, databases, and integration with multiple data sources. While not performing all technical tasks directly, the Data Automation Manager ensures that solutions meet organizational standards, donor requirements, and best practices in data security and responsible data management.

This position requires a balance of technical expertise, strategic thinking, team leadership and stakeholder engagement to ensure that data is transformed into actionable insights that strengthen organizational performance and showcase the collective impact of Prosper Global and its partners.

Essential Responsibilities

Strategic leadership and team management

• Lead and manage the Data Automation Team, including recruitment, onboarding, supervision, and professional development.
• Develop team workplans, priorities and delivery timelines aligned with organizational and portfolio needs.
• Establish and manage a transparent process for intake, prioritization and delivery of data and reporting requests across Prosper Global.
• Foster collaboration across technical, programmatic and operational teams, ensuring clear roles and responsibilities for data management, quality assurance and reporting.
• Build strong working relationships with partner organizations to support effective integration and use of partner-generated data.
• Provide technical oversight and guidance to ensure high-quality deliverables and adherence to organizational standards and best practices.
• Promote a culture of accountability, innovation, learning and continuous improvement within the team.

Data infrastructure, Integration and analytics

• Oversee the design, implementation and continuous improvement of Azure-based analytical infrastructure on Azure to collect, store, integrate, process and analyze data from multiple internal and external sources.
• Ensure the integration and harmonization of data from Prosper Global systems, partner organizations and other relevant platforms into coherent portfolio-level datasets.
• Ensure effective ETL processes (extract, transform, load) using SQL, Python, and other tools.
• Oversee the development and maintenance of dashboards, data products and visualization tools that provide timely and actionable insights to stakeholders, taking into consideration data protection requirements.
• Coordinate integration of Azure solutions with Prosper Global IT systems, including SSO and third-party data sources.
• Ensure optimal performance, reliability, scalability and security of databases, data pipelines and reporting systems.
• Support the organization’s ability to analyze and report results at project, program and portfolio levels through standardized and well-governed data structures.

Data Governance, security and compliance

• Implement and maintain data governance frameworks, standards and controls that ensure the integrity, consistency and appropriate use of organizational data.
• Implement data protection measures in line with Prosper Global’s Responsible Data Protection and Privacy Policy, AI Policy and Ukrainian data protection law, including data minimization, anonymization of personal identifiers, defined retention periods and Privacy Impact Assessments for new systems.
• Ensure appropriate and compliant use of generative AI and emerging tools are used in accordance with organizational policies (e.g. AI Policy) and adherence to data protection standards.
• Implement and maintain robust security protocols for sensitive and confidential data.
• Ensure compliance with organizational, donor and regulatory requirements related to data management and information security.
• Collaborate with the other Prosper Global and partner teams to recognize and adopt best practices in data management, reporting, analysis, and data science.

Data quality, standards and documentation

• Lead the development and maintenance of portfolio-wide data standards, definitions, taxonomies and documentation to ensure consistency across projects, programs and partners, including: Portfolio Master Data List (indicator definitions, KPI IDs, SADD categories, sectors, grant types), Data Automation Plans (DAP) and data collection form rules.
• Set up and run data quality checks with MEL — completeness, valid ranges, consistency, duplicates and outliers — and share regular anomaly reports for data verification.
• Lead season close-out: export, clean and archive one frozen, documented master dataset per program, and combine programs into one portfolio dataset with a common participant ID.
• Make sure every dataset and pipeline has a codebook, cleaning log, README and named owner, and provide documented standard extracts so teams receive routine data without writing scripts.
• Support the creation and maintenance of integrated portfolio datasets that enable consolidated analysis, performance monitoring and impact reporting.
• Ensure that all data products, databases and automated processes are appropriately documented, version controlled and maintainable.
• Develop standardized reports, dashboards and data extracts that improve access to information and reduce manual reporting burdens.
• Champion the use of data visualization and business intelligence tools to communicate progress, results and impact to internal and external stakeholders.
• Ensure data and analysis are accessible and actionable for decision-makers across all levels of the organization.

Supervisory Responsibility The Data Automation Manager directly supervises the Data Automation Team: one Data Engineer and two Data Technical Specialists.

Minimum Qualification & Transferable Skills

• 5+ years of experience in data management, data engineering or analytics, including at least 2 years leading a technical team.
• Working knowledge of SQL and Python, sufficient to review the team’s code, understand data pipelines and set clear technical tasks.
• Practical experience designing and running data management systems (databases, data lakes, data warehouses) and automating data workflows, including deploying scripts and using Git for version control. Experience with Azure data services (e.g., Azure SQL, Azure Data Factory, Azure Data Lake Storage) is strongly preferred.
• Experience creating and managing dashboards, preferably in Power BI (Power Query, DAX); working knowledge of SharePoint / Microsoft 365.
• Experience setting up data quality management and data governance: standards, validation rules and documentation.
• Knowledge of personal data protection requirements (GDPR and Ukrainian law).
• Understanding of MEL data: indicators, baseline and follow-up (PDM) data, disaggregation by sex, age and disability. Experience in international development or economic recovery programming is an asset.
• Proven ability to explain technical issues to non-technical colleagues and to train staff and partners.
• Experience integrating and managing data from multiple organizations, partners or external stakeholders is strongly preferred.
• Strong team coordination, listening and consensus-building skills; able to manage multiple priorities and deadlines.
• Experience working with geospatial data is preferred.
• Full working proficiency in both oral and written English and Ukrainian.

Success Factors

The successful candidate combines strong technical understanding with strategic leadership and a service-oriented mindset. They are a patient translator between technical and program teams: explains data quality in plain language, prioritizes openly and can say no, prefers simple and documented solutions over complex ones, and builds a team that others find easy to work with.

Living Conditions / Environmental Conditions

The position is based in Kyiv, Dnipro or Lviv and requires occasional travel to program locations, which may include areas where freedom of movement is limited.

Deadline for submission of applications: 15 November 2026

Тільки попередньо відібрані кандидати будуть запрошені на співбесіду.

Ласкаво запрошуємо осіб з інвалідністю та ветеранів відгукнутись на цю посаду.

Prosper Global створило робоче місце для працевлаштування осіб з інвалідністю та ветеранів, та належні умови праці для цієї вакансії, але це не обмежує коло осіб, які можуть подаватись на цю вакансію.