Data Engineer

Role Overview

Moringa is building out a dedicated Business Intelligence function, and this hire sits at the technical heart of it. Day to day, you will take raw data scattered across admissions, marketing, operations and finance systems and turn it into pipelines, models and dashboards that leaders can actually rely on when they make decisions. You will be the primary technical owner of the internal BI platform, pairing closely with a BI Analyst and regularly with department heads to work out which business questions need answering and what it takes to answer them well.

This is a hands-on, end-to-end engineering position: you own the problem from the messy source extract through pipeline design and data modelling, right up to the interactive dashboard a non-technical colleague opens on a Monday morning. Because decisions about students, revenue and operations depend on the numbers you produce, the reliability and clarity of your work has a direct effect on how well the organisation runs.

Key Responsibilities

• Build and run data pipelines: design, develop and maintain ETL/ELT workflows that move data reliably from source systems such as admissions, finance, operations, Salesforce and other internal tools into the BI platform.
• Automate ingestion and transformation: replace manual reporting effort with scheduled, repeatable processes that reduce the risk of human error and free up analyst time.
• Keep pipelines healthy: monitor performance, set up alerting for failures and data quality problems, and troubleshoot production issues quickly so reporting is not disrupted.
• Develop the BI platform: build and extend internal applications using Python web frameworks (Django or Flask) with Plotly Dash for interactive visualisation, and look after deployment, environment configuration, versioning, containerisation and CI/CD.
• Design dashboards people can self-serve: create fast, visually clear interfaces that let non-technical stakeholders answer routine questions without raising a ticket, and keep improving their performance, security and usability as data volumes grow.
• Own the data model: build, optimise and document dimensional structures such as star or snowflake schemas, set naming conventions and modelling standards, and tune database design and queries so reports stay responsive at scale.
• Translate business needs into data products: gather requirements with the BI Analyst, finance, admissions and operations teams, then turn those conversations into well-structured, maintainable deliverables, and explain technical trade-offs in plain language to leadership.
• Champion governance and documentation: enforce data quality, access controls and security practices, maintain clear records of sources, definitions and transformation logic, and identify redundant reports or overlapping sources that can be consolidated or retired.

Requirements & Qualifications

• A bachelor's degree in Computer Science, Information Technology, Data or Software Engineering, Statistics or a closely related discipline, or equivalent practical experience.
• Six or more years of professional experience in data engineering, analytics engineering or a comparable software and data role.
• Strong Python skills, with a track record of shipping production-grade applications or services rather than one-off scripts and notebooks.
• Hands-on experience building internal tools or platforms with Django and/or Flask; exposure to additional programming languages is welcome.
• Practical experience creating dashboards and visualisations with Plotly Dash, or the demonstrated ability to pick up an equivalent framework quickly.
• Strong SQL ability, including designing and optimising relational schemas and queries.
• Proven experience building ETL/ELT pipelines end to end, covering scheduling, orchestration and error handling.
• A solid grasp of data modelling principles: dimensional modelling, normalisation, star and snowflake schemas.
• Experience working directly with non-technical stakeholders to scope requirements and deliver tools they genuinely use.
• Experience putting automated data testing and quality assurance frameworks in place.
• Comfortable owning a data product from pipeline through dashboard to stakeholder communication, and able to judge when to move fast versus when to invest in long-term maintainability.
• Strong written and verbal communication, with the ability to make technical detail understandable to audiences of varying technical fluency.
• Meticulous about accuracy, consistency and documentation, and able to collaborate across departments, with leadership and with operational teams.
• Keen to keep learning as tools and business requirements evolve, and to document processes in a way the wider team can follow and build on.
• Nice to have: workflow orchestration tools such as Airflow, Prefect or Dagster; cloud platforms and services (AWS, GCP or Azure) and cloud-hosted databases or warehouses; Git and collaborative workflows including code review and pull requests; Docker and CI/CD exposure; Power BI or Tableau; front-end basics in HTML, CSS or JavaScript; experience mentoring junior engineers or analysts; familiarity with AI and machine learning concepts for automation and predictive insight; prior work in the education sector or with admissions, operations and finance data; knowledge of data governance and privacy standards such as those set by the ODPC.

What We Offer / Why Join

Moringa is a well-established name in Kenya's tech and education landscape, but the working culture still moves like a start-up. The team is made up of mission-driven professionals who care deeply about giving students the best possible experience, and the organisation recognises that this only happens when its people are motivated and supported.

• A hybrid working environment that blends time on site with time working remotely.
• A culture built on four shared commitments: collaboration toward a common goal, keeping the customer at the centre of decisions, personal accountability and ownership, and delivering excellence.
• A results-oriented, collaborative and customer-focused atmosphere, with room for a healthy dose of fun alongside the work.
• The chance to shape a BI function from an early stage, with real influence over the data stack, modelling standards and the tools the whole organisation depends on.