Accountabilities:

Data Management and Infrastructure: Develop, maintain, and improve digital data collection systems, automated data pipelines, and data transformation workflows using tools such as SurveyCTO, Google Sheets, Airbyte, BigQuery, and dbt.
Ensure data availability, consistency, accuracy, and usability across different systems by maintaining data models, troubleshooting technical issues, and improving infrastructure reliability and cost-effectiveness.
Data Quality, Analysis, and Reporting: Design and implement data quality checks, automated validations, and monitoring mechanisms to identify discrepancies, investigate root causes, and support timely issue resolution.
Analyze programmatic and operational datasets, develop dashboards and reports, and generate actionable insights to support organizational monitoring, evaluation, reporting, and decision-making.
Data Governance and Security: Support data governance practices, including access controls, data storage, backups, security, and documentation, ensuring responsible data management and compliance with internal policies.
Conduct data audits and identify opportunities to improve existing systems, streamline manual processes, and introduce automation, AI, and other relevant technologies.
Project Implementation: Contribute to predictive premix stock monitoring by analyzing historical stock, production, and consumption data to identify potential stockouts, ageing inventory, and reporting discrepancies.
Support the implementation of data systems audit recommendations by strengthening data security, access management, auditability, and long-term data management practices.
Collaboration and Technical Support: Work closely with quality, program, research, and operational teams to understand requirements and develop practical data solutions.
Provide technical guidance on data collection tools, reporting systems, and data interpretation, while supporting research and evaluation activities through data preparation, validation, and analysis.
Document workflows, communicate progress, and contribute to continuous improvements in organizational data systems and processes.

Requirements

A Bachelor's degree or higher in Computer Science, Information Technology, Data Science, Statistics, Engineering, or another relevant discipline. Candidates from other academic backgrounds with strong technical skills and relevant experience are also encouraged to apply.
At least 2 years of experience managing the end-to-end data lifecycle, including data collection, processing, transformation, analysis, and reporting.
Strong proficiency in advanced SQL and spreadsheet applications such as Microsoft Excel or Google Sheets, including complex queries, formulas, data manipulation, and analytical techniques.
Familiarity with data collection platforms, data integration tools, cloud data warehouses, and transformation technologies such as SurveyCTO, Airbyte, BigQuery, and dbt is an advantage.
Strong analytical and problem-solving skills, with the ability to investigate data inconsistencies, identify root causes, and develop practical solutions.
Ability to translate business and operational requirements into structured tasks and deliver accurate, well-documented outputs within agreed timelines.
Excellent organizational and project coordination skills, including the ability to define actionable tasks, monitor milestones, and coordinate with relevant stakeholders.
Strong attention to detail, accountability, and ownership when managing datasets, completing assignments, and maintaining technical documentation.
Effective communication skills in English, both written and spoken, with the ability to explain technical issues, analytical findings, data limitations, and project progress clearly.
Ability to collaborate with cross-functional teams, understand different operational needs, incorporate feedback, and support colleagues in using data tools.
A proactive learning mindset, with curiosity and willingness to explore new technologies, analytical methods, AI applications, and automation solutions while critically evaluating their accuracy and limitations.

How Jobgether works

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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