Job description

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.
How do we support and benefit our employees: Competitive salary and stock options — everyone shares in what we're building 25 days holiday + public holidays Fully equipped setup from day one (no waiting for laptops) Regular company offsites and team socials A flat, transparent culture with direct access to leadership At Pixaera, we're committed to building a workplace where everyone feels respected, supported, and empowered to thrive.
We believe that diverse perspectives fuel creativity and innovation, which is why we celebrate individuality and foster an environment of inclusion and belonging.
We're proud to be an equal opportunity employer — discrimination of any kind has no place here.
No matter your background, identity, or lived experience, you're welcome at Pixaera.
Skills / Experiences Core Significant professional experience as a Data Engineer , senior enough to own a platform and its customer-facing outputs on your own.
Proven ability to independently master new concepts and technologies.
Strong skills in analysing business processes and modelling data for reporting.
Proven ability to communicate complex technical concepts and trade-offs to non-technical audiences.
Excellent written and spoken English.
Self-motivated, independent and proactive; able to thrive in a fully remote environment.
AI-native: fluent with agentic coding tools such as Claude Code on real deliverables, and keen to build AI and agentic steps into data pipelines and tooling.
Data tech Strong proficiency in writing Python and SQL.
Strong grounding in data structures, algorithms, and system design.
Proficiency with data warehousing tools like Snowflake and data transformation tools like dbt.
Comfortable modelling and delivering customer-facing dashboards in a BI tool such as Omni , Looker, Metabase or similar.
General tech Solid software engineering practices: testing, code review, CI/CD.
Experience deploying data solutions to production environments .
Experience with performance optimization and cost control in data pipelines.
Experience with one or more public clouds (like AWS, Google Cloud, Azure).
Nice to Have Experience with Omni specifically, or migrating between BI tools.
Backend fluency (Golang, NodeJS, Postgres) to fix data issues at their source.
Setting up and prototyping solutions using AWS; Kubernetes.
Experience working at or with education and/or assessment solutions.