Data Engineer Intern
Zenith Education Studio
Why this role exists
Our data pipelines today run offline - someone kicks off a script, pulls a CSV, cleans it, and the insight is already stale by the time it reaches the team. We're moving that whole workflow to the cloud so our operational data (CRM activity, lesson bookings, student engagement) stays live and queryable without human intervention. You'll help build that foundation from the ground up.
What you'll actually do
Build automated ingestion from our source systems - starting with Trengo (our CRM), then expanding to Google Sheets, Telegram bot events, and internal Postgres databases.
Design and implement ETL pipelines on AWS (Lambda, Glue, Step Functions, or similar — we're open on tooling) that run on a schedule and land clean data in a data lake (S3 + Athena, or equivalent).
Model the data so it's analyst-friendly - think staging → transformed → mart layers, not raw dumps.
Figure out what to put on dashboards, then build them. This is half the job. You'll talk to ops, marketing, and academic staff to understand what decisions they're trying to make, then pick the right tool (Metabase / Looker Studio / Quicksight - TBD) and build dashboards that actually get used.
Document pipelines and data contracts so the next person (including future-you) doesn't have to reverse-engineer anything.
What we're looking for
Comfortable with Python and SQL.
Understands the basics of ETL / data modelling (what a fact table is, why you'd separate raw from transformed data).
Curious about business context - willing to ask "why does this number matter?" before building a chart.
Self-directed: we'll give you problems and context, not step-by-step tickets.
What you'll get out of it
End-to-end ownership of a greenfield data platform - ingestion, storage, modelling, and the dashboards on top. Rare for an intern role.
Direct mentorship from the engineering team; no middle layer between you and the people making architectural decisions.
A concrete portfolio piece you can point to: "I built the data platform that runs X company's live reporting."
A look at how a small-but-growing business actually uses data to make decisions — useful whether you go into engineering, analytics, or startups later.
1000 - 1200 SGD
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