WHO WE ARE LOOKING FOR

Education: Bachelor's degree in Computer Science, Engineering, Statistics, or a related field; equivalent demonstrated experience considered.

Experience: 2 to 4 years in data engineering or backend engineering with substantial data work, in a production environment.

Programming: strong Python and SQL; you write pipelines as software, with tests, not as scripts.

Databases: solid PostgreSQL; exposure to SQL Server is a plus.

Transformation and orchestration: hands-on dbt experience and familiarity with a modern orchestrator; Dagster preferred, Airflow background welcome.

Data movement: working understanding of incremental and idempotent load patterns; familiarity with Kafka and Spark is a valued plus, not a requirement.

Engineering practice: Git discipline, CI/CD, and containerization (for example Docker) as daily habits; documentation you would want to inherit.

Data protection: awareness of handling sensitive personal data responsibly; experience with regulated, financial, or humanitarian data is a strong plus.

Growth: evidence that you seek and act on feedback; this role comes with structured mentorship, and we are looking for someone who will use it.

Communication: ability to explain what a pipeline does, what broke, and what you changed, clearly and in writing.

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.

WHAT YOU’LL GET

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

• Meaningful work that directly contributes to sustainable livelihoods and job creation across East and Central Africa.
• 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
• A dynamic and entrepreneurial team environment committed to innovation and social impact
• 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.

• Build, maintain and operate reliable, auditable data pipelines integrating approved enterprise, lending, programme, survey and external data sources, within the platform architecture set by the Senior Data Engineer.
• Keep all loads idempotent and checkpointed, so an interrupted run resumes rather than restarts, and document every pipeline as code alongside the pipeline itself.
• Enforce column-level minimization at ingestion: personal data that no downstream model needs is never ingested.
• Apply the platform's reusable integration patterns when onboarding new sources, and flag where a pattern does not fit rather than working around it silently.
• Implement tests, contracts, and freshness checks for the pipelines you own, feeding the promotion-blocking quality gate: when a check fails, downstream publication halts and someone is alerted, by design.
• Monitor the health, performance and cost of your pipelines through the platform's observability and alerting, and respond to incidents within agreed SLAs/SLOs.
• Participate in root-cause analysis for pipeline and gate failures, and contribute short, blameless written causes and fixes.
• Implement components of the client entity resolution layer to the Senior Data Engineer's design, including matching logic, survivorship rules, and the auditable record of merge decisions.
• Investigate unresolved or conflicting matches and surface them with evidence, rather than silently picking one.
• Apply the technical controls required by Inkomoko's Data Governance Framework in the pipelines you build, including classification, access, lineage, retention, encryption, minimisation and auditability.
• Work within the platform's data protection controls, aligned with the data protection laws of the jurisdictions we operate in; access administration is centrally managed and this role works inside it, not above it.
• Collaborate with Technology Enablement, Product and Innovation, MERL and business system owners on source-system changes and data dependencies affecting your pipelines.
• Engage actively in mentorship: structured code review, pairing, and a written growth plan with the Senior Data Engineer.

• Python
• SQL
• PostgreSQL
• dbt
• Dagster (preferred)
• Airflow (background welcome)
• Incremental and idempotent load patterns
• Git
• CI/CD
• Docker
• Data protection awareness
• Communication (written and verbal)

• Bachelor's degree in Computer Science, Engineering, Statistics, or a related field; equivalent demonstrated experience considered.
• 2 to 4 years in data engineering or backend engineering with substantial data work, in a production environment.
• Strong Python and SQL skills.
• Solid PostgreSQL experience.
• Hands-on dbt experience.
• Familiarity with a modern orchestrator.
• Working understanding of incremental and idempotent load patterns.
• Experience with Git discipline, CI/CD, and containerization (e.g., Docker).
• Awareness of handling sensitive personal data responsibly.
• Evidence of seeking and acting on feedback.
• Ability to explain technical concepts clearly and in writing.