Data & Analytics Engineer

Mid-level (3–10 years’ experience)

About CambriLearn

CambriLearn is transforming K-12 education for the digital age. As a leading online school offering internationally recognised curricula, we empower students across the globe through flexible, data informed learning experiences.

To scale our impact and improve how we use data across the business, we're hiring a Data & Analytics Engineer (skilled in full stack data science from data pipelines, modelling, deployment to insights) who will own the integrity, usability, and clarity of the data that drives our decision-making.

What You’ll Do

You’ll play a critical role in solving some of our most pressing data challenges. This role isn’t just about dashboards, it’s about fixing the root of broken data, redefining core metrics, and building the pipelines that power every team from Product to Sales to Finance.

• Design and maintain robust data pipelines (ETL/ELT) across platforms such as Salesforce, Google Ads, Meta Ads, Stripe, and CMS systems


• Perform data normalization, cleansing, transformation to align disparate datasets


• Map and integrate data from CMS, CRM, Google Ads, Meta Ads, and other platforms


• Identify hidden relationships across datasets


• Proactively identify data gaps and quality issues and implement fixes


• Integrate AI tools into internal workflows and identify areas of the product where AI can be included.


• Define and monitor KPI's across departments


• Conduct analysist to support product, marketing, sales and other strategic decisionsInvestigate and resolve data integrity issues across products, users, conversions, and retention.


• Redefine and implement accurate business metrics (e.g. what constitutes a conversion, per subject, per class, per level).


• Build and maintain robust data pipelines (SQL + Python) to transform raw data into structured, reliable datasets.


• Design and deploy interactive Power BI dashboards that help teams make faster, better decisions.


• Collaborate across departments (Product, Sales, Marketing, Finance, Ops) to understand data needs and build scalable solutions.


• Build and document relational data models that reflect the reality of our business and customer journeys.


• Assist in implementing data governance, ownership protocols, and best practices for scalable analytics.


• Drive a company wide shift toward data transparency, consistency, and confidence in reporting.

Our Stack

We don’t expect you to know everything but you should be comfortable with or excited to learn:

• SQL (PostgreSQL, BigQuery, or similar)


• Python for scripting and transformation


• Power BI for reporting and dashboarding (bonus if you know DAX or row-level security)


• Salesforce (CRM data integration and reporting)


• Heroku hosted Ruby on Rails app (you’ll be working with its data outputs)


• AWS for content and infrastructure (S3, databases, etc.)


• Bonus: experience with DBT, Airflow, or orchestration tools for pipeline management

Who You Are

• 3–10 years of experience in Data Engineering, Analytics Engineering, or BI focused data roles


• Proven track record of solving real business problems through data


• Able to work with messy or unreliable datasets and design systems that make them trustworthy


• Collaborative and curious: you love working with different teams and asking why?


• Comfortable translating non-technical requests into scalable, accurate data products


• Obsessed with clean, maintainable, scalable systems and not one-off solutions

Preferred Educational Background

We’re specifically looking for candidates with a Bachelor’s or Honours degree in:

• Industrial Engineering


• Information Engineering

These degrees offer the perfect balance of technical depth, systems design, and business process understanding which is exactly what this role requires.

Why Join CambriLearn

• Make a meaningful impact on the future of education


• Join a smart, mission driven team that values autonomy, speed, and excellence


• Work from anywhere in SA (remote first)


• Help build the data foundation for a company with massive growth potential