Data & Analytics Engineer

Location: Nairobi, Kenya
Department: Data & Analytics
Reports To: Senior Manager, Data & Analytics
Job Type: Fixed Term Contract
Working Model: On-site, 5 days a week
Salary: Competitive, based on experience
Travel Requirements: Occasional domestic travel up to 10%

About Food for Education
Food4Education is an award-winning, African-led nonprofit tackling classroom hunger with a locally rooted, scalable model. Building on more than a decade of learning by doing, we’re powering a new school feeding industry and sharing our blueprint to scale sustainable, nutritious and affordable school feeding programs across Africa. Today, we serve over 600,000 learners daily in Kenya, but what we deliver goes beyond the meal. Each plate improves nutrition, fuels learning, and creates jobs that uplift entire communities. We are an experienced, trusted non-profit partner that operates with the excellence of a global business, reinvesting the value we create into local economies.

Over the past decade, F4E has scaled its reach exponentially, serving 160 million cumulative meals since its inception, and growing from just 25 children fed daily in 2012 to over 600,000 learners receiving meals every single day in 2026. With our presence now spanning 13 counties, we’re delivering daily meals to children in 1,650+ public schools and ECD centers. Parents pay for these meals through a mobile money system linked to NFC wristbands, which their children wear and ‘Tap2Eat’ in under 5 seconds to access their meal.

F4E is growing quickly. Our mission is to scale a model that prioritises efficient supply chain management and sustainable sourcing, so we can continue lowering the cost of school meals. We have served over 160,000,000 meals since 2012 and are expanding to reach 1 million learners in Kenya by 2027 and another 2 million across Africa by 2030.

Our Values
At Food for Education, our values are guiding principles that provide us with purpose and direction and set the tone for our interactions with all stakeholders:

• Build with excellence and curiosity - We’re not afraid to try new things and iterate as much as we can to find the best and most efficient way to get results;
• Be the change you seek - We acknowledge that continuous improvement is a shared responsibility;
• We do what we say; and say what we do - We embrace an ownership mentality;
• Ask why; and commit - Share openly and question respectfully and commit fully. When we understand the why, we are able to work with a purpose.

About the Role
The Data & Analytics Engineer owns Food4Education's data platform end to end: the pipelines and APIs that bring data from source systems into the data warehouse, and the models, tests and definitions that turn it into metrics the organisation can rely on. The role ensures data arrives reliably, completely and securely; is modelled consistently so every report returns the same answer; and is documented to a standard that supports multi-country expansion and technical assistance to partner organizations. The post-holder works in a two-person engineering team in which each member leads one discipline and is fully capable in the other, working closely with engineering and platform teams, source-system owners, BI analysts and business teams.

Key Responsibilities

• Data architecture and source assessment: Document and profile all data sources — relational databases, Google Sheets, APIs and unstructured data — for quality, volume, update frequency, key relationships and business entity mappings. Design and maintain the unified BigQuery data model, applying agreed naming and governance standards, partitioning and clustering for cost, and retention and historisation rules, designed for transfer across countries and partners.
• Pipeline development and orchestration: Build and maintain extraction, transformation and enrichment pipelines for every source system, using incremental loading to minimise processing cost, and deliver data migrations, new integrations and ingestion for new countries. Configure and maintain Apache Airflow (or equivalent) workflows with business-aligned scheduling, error handling, retries and backfills, and monitor pipeline health to resolve failures.
• Analytics engineering and metric modelling: Design and maintain dbt models from staging to serving layers with consistent grain, naming and conformed dimensions. Implement core metric definitions so every report, dashboard and external submission uses the same logic; build dbt tests across critical assets; maintain the KPI dictionary (definition, logic, source, refresh cadence, as-at date, businessowner); reconcile figures where systems disagree; prepare certified self-service datasets; and flag definitions that cannot be implemented as written, working with system and business owners to close gaps at source.
• Data quality, protection and incident management: Implement validation checks at extraction and loading. Maintain quality monitoring dashboards, data dictionaries, alerting tools, and data lineage, while logging, triaging, resolving, and documenting incidents against agreed severity levels. Mask or hash personal data at the ETL layer, implement row- and column-level access control across agreed tiers, ensure no model reintroduces personal data, and support access reviews and data protection requirements.
• Documentation and knowledge transfer: Maintain the raw-layer data dictionary, KPI dictionary, dependencies and lineage; document pipelines, transformations, models and operational runbooks; train and support the BI team on data models and access patterns; and ensure systems can be operated and transferred without the post-holder present.

Minimum Requirements

Education:

• Bachelor's degree in Computer Science, Engineering, Statistics or a related field.

Experience:

• Minimum 4 years across data and analytics engineering, with production experience in both, including at least 2 years owning dbt and Big Query in production (models, tests and documentation) and demonstrated delivery of data migrations.

Skills & Competencies:

• Strong Python and SQL
• Advanced proficiency in BigQuery or an equivalent cloud data warehouse in production
• Dimensional modelling: grain, conformed dimensions, slowly changing dimensions and star schema design
• Production experience building and orchestrating data pipelines with tools such as Apache Airflow, Dagster, Cloud Composer or GitHub Actions, including scheduling, dependency management, retries and alerting
• Change data capture, incremental loading and backfill strategies across varied source systems
• Version control, code review and CI/CD applied to data work (GitHub or equivalent)
• Data protection controls and data migration procedures
• Able to translate a business metric definition into an implementable specification, and discuss it directly with non-technical stakeholders
• Attentive to data accuracy; documents as a matter of course and builds systems others can operate
• Raises problems early and is comfortable reporting known issues and quality gaps
• Communicates clearly with non-technical colleagues, system owners and vendors
• Organized and dependable under operational pressure

Certifications (if applicable):

• Cloud data platform or dbt certifications are an advantage but not required.

Preferred Qualifications

• ERP integration experience, Sage X3 or similar IoT or telematics data
• Experience supporting month-end financial close, ensuring finance data feeds are complete, reconciled and available on schedule
• Experience in a small team owning the full data stack

What Success Looks Like

Within the first 12 months:

• Data migrations and data integrations live within the expected timelines.
• New ingestions running on standard patterns rather than a bespoke build.
• Pipeline uptime above 90%, with alerts responded to within 4 hours.
• Failures caught by monitoring before a stakeholder reports them.
• Data and KPI dictionary covering more than 80% of core datasets.
• Personal data masked at source and access tiers in place across all reporting.
• Dependencies and governance based on business logics implemented on core datasets.
• Every incident closed with a documented root cause within 5 working days.

What is in it for you?
We have a strong culture of constant learning and we invest in developing our people. You will have weekly check-ins with your manager, and regular feedback on your performance. We hold career reviews every six months and set aside time to discuss your aspirations and
career goals. You will have the opportunity to shape a growing organization and build a rewarding, long-term career.

Join Us
To apply, please submit your updated CV and answer the application questions listed. All applicants will receive communication on the outcome of their application, regardless of outcome.
We are committed to building an inclusive workplace where diverse perspectives are valued and people are supported to do their best work. We welcome applications from candidates of all backgrounds and lived experiences and make employment decisions based on merit, potential, and alignment with our values.