Data and Reporting Manager

BACKGROUND

About Hatch Africa

Founded in 2010, Hatch Africa is the leading dual-purpose poultry (DPP) company in sub-Saharan Africa and one of the highest impact businesses on the continent. In 2022, the group distributed over 70m dual-purpose day-old chicks (DOCs) to smallholder farmers in Ethiopia, Rwanda, Uganda, Ghana, Kenya, and Ivory Coast through its subsidiaries, thereby making a significant improvement in nutrition and incomes of local populations. The Company has strong ESG practices and has been backed by leading institutional investors.

About EthioChicken

EthioChicken was the first business in Hatch Africa's portfolio, founded in 2010. Today, EthioChicken is a leading distributor of chickens to rural farmers in Ethiopia with a vision to provide one chicken per person per year through smallholder farmers. We are a rapidly growing Company that believes in investing in our employees and offers them opportunities for career advancement and is committed to female empowerment across the company. EthioChicken is an Ethiopian based company.

OUR VISION

To provide one chicken per person per year through smallholder farmers.

OUR PURPOSE

To improve the livelihoods of smallholder farmers by providing quality poultry products and services.

Job Summary

The Data and Reporting Manager and grows a team of reporting analysts and data engineers. This role is responsible for the design, development, and optimization of Hatch Africa's data infrastructure, built primarily on Microsoft Azure and Google Cloud Platform, ensuring the pipelines, data lakes, and warehouses that feed the team's reporting and analysis are reliable, secure, and scalable. The Lead balances hands-on analytical and technical leadership with team management, stakeholder engagement, and ownership of the broader reporting, analytics, and data infrastructure roadmap.

Role KPIs

• ≥90% satisfaction score from internal stakeholder surveys of report and analysis “customers” (end-user departments)
• 99% uptime of reports, interactive analytical tools, and data pipelines
• 100% accuracy of reports and analytical outputs
• 95% of reported issues resolved within SLAs set by the team
• Establishment of standardized data governance practices across all markets within 12 months
• Successful onboarding and development of at least 2 junior data engineers within the first year

Key Responsibilities

Leadership & Team Management

• Mentor and guide a team of reporting analysts and data engineers, creating a collaborative and high-performing work environment that is conducive to learning and professional development
• including growth in Python-based analysis, LLM-assisted workflows, and data engineering practices on Azure and GCP.
• Encourage innovation and process improvements, fostering a culture where new ideas, tools, and analytical techniques are tested and implemented.
• Provide guidance and support to team members, ensuring alignment with organizational goals and objectives.
• Conduct regular performance evaluations for team members, providing constructive feedback and identifying areas for professional growth, including analytical and technical skill development.
• Identify technical and analytical skill gaps (e.g., SQL, PowerBI, Python, statistical methods, LLM tools, Azure, GCP, ETL/ELT pipelines) and work with Management to define training plans to fill gaps.
• Manage team workload to ensure full utilization and advocate for additional hires, when necessary.

Data Analysis & Reporting

• Conduct in-depth data analysis to extract valuable insights and trends, using Python (e.g., pandas, numpy, statistical and visualization libraries) as the primary analytical toolset, and PowerBI where it is the most effective medium for end-user consumption.
• Design and oversee the development of interactive, code-based reporting tools and applications (e.g., using Python frameworks such as Streamlit or Dash) to give end-users more depth and flexibility than static dashboards.
• Ensure data visualization and interactive reporting are accessible and meaningful, driving key business decisions.
• Establish data standards, analytical methodology, and checklists for the team to ensure consistency and rigor across reports and analysis.

Data Infrastructure & Engineering

• Architect, build, and optimize scalable data pipelines across Microsoft Azure and Google Cloud Platform (GCP) for structured and unstructured data, including data lakes, warehouses, and real-time processing solutions (e.g., Azure Synapse, Big Query, Dataflow).
• Integrate data from diverse systems (ERP, spreadsheets, financial systems, mobile apps) into centralized platforms, defining and enforcing master data standards to ensure comparability (“apples-to-apples”) across markets.
• Monitor and tune data systems for performance, cost-efficiency, and scalability, implementing best practices for storage and retrieval on Azure and GCP.
• Implement data governance practices covering data quality, lineage, security, and access management, ensuring compliance with internal and external regulatory requirements.
• Partner with reporting and functional teams to proactively identify opportunities for pipeline automation and stay current on developments in the data infrastructure space to recommend improvements.

Stakeholder Engagement

• Foster collaborative relationships with stakeholder departments to gather, understand, and translate reporting and analytical requirements into precise, actionable insights, and deliver clean, reliable datasets that power business intelligence and analytics.
• Own the Reporting and Data Team roadmap and facilitate regular communication to manage expectations on deliverables and provide clear reporting, analysis, and data infrastructure specifications.

Strategic Planning and Roadmap Development

• Align the reporting, analytics, and data infrastructure strategy with Hatch Africa's goals, prioritizing based on resource availability and strategic impact.
• Manage and execute a reporting, analytics, and data infrastructure roadmap that effectively manages team workloads and meets the evolving needs of the company, contributing to building a world-class BI and data function across Hatch Africa's multi-country operations.

Process Improvement

• Identify opportunities for process improvement and efficiency in reporting, analytical, and data engineering workflows, ensuring the integrity and security of data used in reporting and pipeline activities.
• Lead initiatives to stay ahead of industry trends, adopting new reporting tools, Python-based analytical techniques, LLM capabilities, and data infrastructure best practices (e.g., CI/CD, testing, and documentation for data workflows) to enhance the team's capabilities.

Qualifications

• Bachelor's degree in information technology, Computer Science, Engineering, or a related field.
• 5+ years of experience in data analytics and/or data engineering roles, with at least 2 years in a managerial role.
• Strong proficiency in Python for data analysis and visualization (e.g., pandas, numpy, matplotlib/plotly); experience building or overseeing interactive, code-based reporting tools (e.g., Streamlit, Dash) is strongly preferred.
• Working knowledge of PowerBI and other data analysis tools, applied selectively alongside programmatic reporting rather than as the default approach.
• Solid experience building and maintaining data pipelines and infrastructure on Azure and/or GCP (e.g., Azure Data Factory, Synapse Analytics, Databricks, Big Query, Dataflow), with strong SQL and database management skills.
• Familiarity with ETL/ELT tools (e.g., Azure Data Factory, DBT) and data orchestration frameworks.
• Proven ability to translate complex data into actionable business insights and recommendations.
• Strong leadership, problem-solving, and communication skills.
• Demonstrated ability to manage cross-functional teams and engage stakeholders effectively.
• Familiarity with REST APIs and generative AI.
• Business Central ERP knowledge and relevant Azure/GCP certifications (e.g., Fabric Data Engineer, Google Cloud Professional Data Engineer) are advantageous.