Data Engineer
full-time
Working at Moringa
We are an established and respected part of Kenya's tech and education ecosystem, yet we retain a fast-paced and dynamic culture that is reminiscent of a start-up. We are all mission-driven professionals with a passion for providing the best student experience possible. And we know that is only possible if our team is highly motivated. We value results, collaboration, and a customer-focused mindset, and offer a healthy dose of fun along with a hybrid working environment.
Moringa Culture Code
Collaboration: We work together for a common goal
Customer Centric: The customer is at the heart of all we do
Accountability: I take ownership
Excellence: I deliver exceptionally
Role Overview
Moringa is investing in a stronger Business Intelligence (BI) function, and this role is central to that
effort. We are looking for a Data Engineer to join our BI team and work closely with our BI Analyst to design, build, and scale the data infrastructure that powers decision-making across the organisation.
This is a full-time, hands-on engineering role for someone who enjoys owning problems end to end. From raw, messy source data, through pipeline design and data modelling, all the way to a polished, interactive dashboard that a non-technical stakeholder can use with confidence. You will be the
primary technical owner of Moringa's internal BI platform, working in a Python-based stack (Django/Flask with Plotly Dash) to turn data from admissions, marketing, operations, and finance into reliable, actionable insight.
You will partner daily with the BI Analyst and regularly with leadership and department heads to
understand what questions the business is trying to answer and translate those questions into robust, scalable data products.
Key Responsibilities
Data Pipelines & ETL/ELT
Design, build, and maintain data pipelines and ETL/ELT workflows that reliably move data from source systems (admissions, finance, operations, Salesforce, and other internal tools) into the BI platform.
Automate data ingestion, transformation, and loading processes to reduce manual reporting effort and minimise the risk of human error.
Monitor pipeline health, build alerting for failures or data quality issues, and troubleshoot production issues quickly to minimise disruption to reporting.
Implement data validation, testing, and quality checks at each stage of the pipeline to ensure trustworthy outputs.
BI Platform Development
Develop and maintain Moringa's internal BI platform using Python-based web frameworks (Django / Flask), with Plotly Dash for interactive dashboards and data visualisations, or other tools as deemed necessary.
Design intuitive, performant, and visually clear dashboards that allow non-technical stakeholders to self-serve answers to common questions.
Continuously improve the platform's architecture, performance, security, and user experience as usage and data volumes grow.
Manage deployment, versioning, and basic DevOps practices (e.g. environment configuration, CI/CD, containerisation) for the BI platform.
Data Modelling & Architecture
Build, optimise, and document data models (e.g. star/snowflake schemas, dimensional models) that provide a single, reliable source of truth for analysts, leadership, and operational teams.
Define and enforce data modelling standards, naming conventions, and documentation practices to keep the data warehouse maintainable as it scales.
Own the underlying database design and query performance, ensuring dashboards and reports remain fast and responsive as data grows.
Stakeholder Collaboration & Reporting
Collaborate closely with the BI Analyst and stakeholders across operations, finance, admissions, and other departments to gather requirements and clarify business questions.
Translate business requirements into scalable, well-structured data products, dashboards, and reports, balancing stakeholder urgency and needs with long-term maintainability.
Present technical concepts and data findings in clear, non-technical language to leadership and operational teams.
Maintain clear documentation of data sources, definitions, transformation logic, and dashboard usage for internal knowledge-sharing.
Data Governance & Best Practices
Champion data quality, consistency, and governance practices across the organisation, including access controls and data security best practices.
Identify opportunities to improve existing data infrastructure, retire redundant reports, and consolidate overlapping data sources.
Stay current with emerging tools and practices in data engineering and BI, and recommend improvements to Moringa's data stack where relevant.
Required Qualifications and Experience
Bachelor's degree in Computer Science, Information Technology, Data/Software Engineering, Statistics, or a related field (or equivalent practical experience).
6+ years of professional experience in data engineering, analytics engineering, or a closely related software/data role.
Strong proficiency in Python, including experience building production-grade applications or services (not just scripts/notebooks).
Hands-on experience with Django and/or Flask for building internal web applications or platforms. Experience in other programming languages is a plus.
Practical experience building dashboards or data visualisations with Plotly Dash (or a strong willingness and ability to ramp up quickly if experience is with a comparable framework).
Experience working with other tools for creating dashboards and reports such as Power BI or Tableau is a plus.
Strong SQL skills and demonstrated experience designing and optimising relational database schemas and queries.
Proven experience designing and building ETL/ELT pipelines, including scheduling, orchestration, and error handling.
Solid understanding of data modelling concepts (dimensional modelling, normalisation, star/snowflake schemas).
Experience working directly with non-technical stakeholders to gather requirements and deliver usable data products.
Experience implementing automated data testing and quality assurance frameworks.
Preferred / Nice to have Skills
Experience with workflow orchestration tools (e.g. Airflow, Prefect, Dagster, or similar).
Familiarity with cloud data platforms and services (e.g. AWS, GCP, or Azure) and cloud-hosted databases or data warehouses.
Experience with version control (Git) and collaborative development workflows (code review, pull requests).
Exposure to containerisation and deployment tools (Docker, basic CI/CD pipelines). Experience in the education sector, or with admissions/operations/finance data specifically.
Familiarity with front-end basics (HTML/CSS/JavaScript) for polishing internal dashboards and applications.
Experience mentoring junior engineers or analysts.
Familiarity with AI and machine learning concepts or frameworks to leverage data automation and predictive insights
Knowledge of data governance, security best practices, and privacy standards (e.g., ODPC).
Key Competencies
Ownership mindset. You must be comfortable owning a data product end-to-end, from pipeline to dashboard to stakeholder communication.
Strong communication skills. You should be able to translate technical detail into clear, actionable insight for non-technical audiences.
Attention to detail. We are rigorous about data accuracy, consistency, and documentation, and you should be too.
Pragmatic problem-solving. You should know and understand how to balance speed of delivery with long-term maintainability of data infrastructure.
Collaborative. You need to be able to work well across many departments, with leadership, and other operational teams with differing levels of technical fluency.
Adaptability & Continuous Learning. Ability to stay current with new data engineering tools and adapt to evolving business requirements.
Documentation & Knowledge Sharing. Proven ability to document technical processes in a way that is accessible to the broader team, ensuring long-term scalability.
Data Product Mindset. A focus on viewing data pipelines as "products" that prioritize reliability, user experience, and continuous improvement for the end-user.