Description:
How you'll role
The client is transforming K-12 education for the digital age. As a leading online school offering internationally recognised curricula, they empower students across the globe through flexible, data informed learning experiences. To scale their impact and improve how they use data across the business, they’re hiring a Data Engineer who will own the integrity, usability, and clarity of the data that drives their decision making.
What you'll do
You’ll play a critical role in solving some of their 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.
Responsibilities include
- Investigate 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
Tech stack 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
Requirements:
- Investigate 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
- 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
- Data Analysis: 4 to 5 years
- Sql: 4 to 5 years
- Python: 4 to 5 years
- Power Bi: 4 to 5 years
- 5–10 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
- Industrial Engineering
- Information Engineering
What you'll need
- 5–10 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
Bachelor’s or Honours degree in
- Industrial Engineering
- Information Engineering
08 May 2025;
from:
careers24.com