Data Engineer

Who are we?

We are a team of driven individuals who strongly believe in the positive impact gaming and AI will have on the learning world. Today, we’re helping enterprise businesses transition from video to gamified learning experiences that far outperform their traditional counterparts. If you strive to work in a creative and high-output environment, read on.

Who are we looking for?

A senior data engineer to own Pixaera's data end to end: the pipelines that bring data in, the warehouse and transformations that shape it, and the customer-facing dashboards and insights we build on top. Our customers judge the value of their training by what they can see, so this role owns that surface directly. Today the stack is Fivetran into Snowflake, transformed with dbt and surfaced through Omni. You will take real ownership of it, fix what is brittle, and turn it into a genuine product surface rather than a side project. You are happy working across the backend to solve data problems at their source, and you can explain a trade-off to a customer success lead as clearly as to an engineer.

What you will own
- Customer-facing dashboards and reporting: the activity, completion and performance views customers rely on, built on the current data model (courses and completions, not legacy sessions) and kept correct as new content ships.
- The data platform end to end: ingestion (Fivetran), the warehouse and data lake (Snowflake) and the transformation layer (dbt), including the modelling that harmonises sources and versions data properly.
- Turning raw learning and assessment data into insights that customers and internal teams can act on, and moving us toward live and near-real-time reporting.
- Reliability and cost: monitored, well-behaved pipelines, sensible incremental versus full-refresh models, and a real handle on data spend.
- Data products beyond dashboards: APIs, reports and exports, and the content mappings that keep reporting accurate, owned inside the publish pipeline rather than as manual handoffs.
- The data layer in product design: partnering with backend and frontend engineers so new features integrate with data cleanly from the start, and raising the bar for data practice across engineering.