Senior Data Engineer

Inkomoko is an affirmative action/equal opportunity employer.  Refugees, women, and persons who reflect the diverse communities we serve are strongly encouraged to apply.  

ABOUT THE OPPORTUNITY AND RESPONSIBILITIES

As a Senior Data Engineer, you will play a strategic role within the MERL team, and you will report to the Business Analytics Manager. You will lead the architecture, development, optimization and maintenance of scalable, reliable, and secure data platforms, engineering robust batch and real-time data pipelines that power business analytics, reporting, and data-driven applications across Inkomoko’s countries of operation.

You will collaborate closely with the Digital Transformation team (IT), Data & Quality Analysts, the Business Analytics Manager, and country MERL teams to ensure data pipelines are efficient and datasets are clean, accessible, well-documented, and ready for analytics, reporting, and decision-making. Success in this role requires strong data pipeline engineering and analytics skills for technical execution, attention to data quality, process documentation, and the ability to collaborate effectively across teams. This position is based in Rwanda, Ethiopia, South Sudan, Chad, or  Kenya.

KEY RESPONSIBILITIES

1. Data Pipelines & Integration (30%)

• Own the architecture, design, and evolution of scalable, secure, and reliable data solutions that enable data-driven decision-making.
• Lead the design and implementation of real-time, event-driven data pipelines using technologies such as Debezium (CDC), Apache Kafka, and similar streaming platforms to integrate data from internal systems, ERP platforms, and data collection tools (e.g., SurveyCTO).
• Lead the development and maintenance of scalable batch data ingestion pipelines using modern data integration tools, preferably Airbyte.
• Build and maintain centralized, high-quality datasets that support analytics, reporting, and AI initiatives across country and regional programs.

2. Data Modeling, Storage & Security (20%)

• Lead the design and governance of scalable data models, with a strong emphasis on dimensional modeling and analytics ready data models.
• Own the design, development and maintenance of secured, performant, scalable, and reliable OLAP (ClickHouse) and OLTP (MySQL/PostgreSQL) platforms.
• Automate database replication via CDC workflows  to ensure data consistency and enable fast, reliable recovery in failure scenarios.
• Lead data security and governance process  by implementing RBAC, encryption, backups,  disaster recovery, and secure access controls.

3. Data Quality & Monitoring (20%)

• Lead the design of data validation frameworks using dbt and Great Expectations (GX), and drive automation of data-quality processes.
• Establish anomaly detection, outlier monitoring, and reporting practices to guarantee dataset reliability.
• Document and continuously improve process flows for outlier resolution; train and support program teams on data-quality standards.
• Set the standard for pipeline-to-validation alignment in close partnership with Data Quality Analysts and other data team members.

4. Data & System Observability and Monitoring (10%)

• Design and implement observability for infrastructure, data pipelines, and data warehouse performance using tools such as Prometheus and Grafana.
• Define and track key operational metrics in real time, pipeline latency, throughput, failure rates, resource utilization, and data freshness.
• Build alerting and dashboards that surface pipeline or infrastructure degradation early, reducing time-to-detect and time-to-resolve for incidents.

5. Infrastructure Management, DevOps & Automation (10%)

• Own the setup and configuration of on-premise virtual machines and supporting services that host data pipelines, data warehouses, and databases.
• Lead the design and management of CI/CD pipelines for automated data testing and validation using tools such as dbt and Great Expectations, ensuring reliable, consistent, and repeatable dataset production, as well as automated infrastructure provisioning and deployment of data workflows.

6. Documentation, Mentorship & Learning (10%)

• Maintain clear, high-quality technical documentation covering database/schema design, data lineage, and ETL/ELT processes.
• Mentor and coach junior data engineers; lead knowledge-sharing sessions and set engineering best practices for the team.
• Stay current with, and champion the adoption of, emerging tools and practices in data engineering and analytics infrastructure.

WHO WE ARE LOOKING FOR

• Education: Bachelor’s degree in Computer Science, Engineering, Data Science/Statistics, or a related field; a Master’s degree is a plus.
•  Experience:  5+ years of experience in data engineering, data management, or analytics infrastructure, with demonstrated experience in leading data platforms end-to-end.
• Programming & Scripting: Strong proficiency in Python, SQL, and Bash/Shell.
• Data Modeling: Proven experience with dimensional modeling and designing data models optimized for analytical workloads at scale.
•  Data Quality Assurance: Hands-on experience building and scaling data testing and validation frameworks with dbt and Great Expectations (GX).
•  ELT/ETL & Ingestion Tools: Strong knowledge of Apache Airflow, dbt, and ingestion tools such as Airbyte, candidate must also possess hands-on experience working with webhooks, and API.
• Modern database and data warehouse : Experience owning OLTP and OLAP (ClickHouse) database development and maintenance  in production.
• Streaming & Big Data: Experience with Debezium (or equivalent CDC tooling), and  Apache Kafka is required, experience with Spark or similar streaming compute is a strong plus.
• Observability: Experience with Prometheus, Grafana, or equivalent open-source observability stacks for infrastructure and pipeline health.
• Infrastructure setup, CI/CD, Containerization & Version Control: Strong hands-on experience in setting up and managing virtual machines, with proven expertise in CI/CD pipelines, Git, and Docker in production on-premise environments
• Leadership & Collaboration: Demonstrated ability to mentor junior data engineers, lead technical decisions, and communicate complex technical concepts clearly to technical and non-technical stakeholders alike.

Key Competencies:

We are looking for someone who;

• Instills Trust – Follows through on commitments, builds credibility by being direct and truthful, and shows genuine care for staff members.
• Acts with Courage – Steps up to address difficult issues and speaks openly with bravery; takes the initiative to pursue new opportunities; takes full ownership of own work
• Makes Informed Decisions – Seeks relevant data and input when needed, takes appropriate action within their area of responsibility, and knows when to escalate issues or seek guidance.

WHAT YOU’LL GET

This role is inside a high-growth, mission-driven social enterprise. By joining, you’ll access:

• Competitive salary, and potential Performance-based bonus
• Incredible company culture, with opportunities for learning and growth
• Diverse colleagues across the region, and policies that demonstrate commitment to equity and inclusion
• Ability to make a significant social impact to your community
• Health insurance for self and family
• Staff savings and provident fund, negotiated bank rates for long-term employees
• Generous annual leave, parental leave, and sabbatical options.

HOW TO APPLY

If you’re excited about this role, please submit your application through the: >> JOBS PORTAL.

Tell us about what you’ll bring to this growing company.

DEADLINE:  17th July 2026. Applications are reviewed on a rolling basis, please apply as soon as possible!

Inkomoko is committed to justice, diversity, equity and inclusion.  As we seek to reflect the communities we serve, refugees and women are strongly encouraged to apply. As a company we have policies that ensure fair treatment in the application process.

NB: Only shortlisted candidates will be contacted. Employment is conditional upon successful background checks and other verification as needed.