and it’s creating real impact.As a category-defining company, we’re shaping what the future of learning looks like at general scale.Every Preply lesson sparks change, fuels ambition, and drives progress that matters.
Joining Preply means helping define the future of education at global scale, and building something that truly matters for millions of people, every day.At Preply, the Data Ingestion and Enrichment team provides a single, trusted, and scalable data foundation.
The team ensures that all analytics, machine learning, and product features are built on unified, governed, and production-grade data assets in Preply's Lake House, including the extraction, normalization, and generation of structured data from Preply's unstructured assets, forming a durable data moat for AI-driven products.As a Data Engineer in the Data Ingestion and Enrichment team, you will build and contribute to the data layer that powers both Preply's analytics, machine learning, and product.
You will work closely with ML Platform, Applied/Data Scientists, Analytics Engineering,



and Product squads to ensure that features, datasets, and pipelines are production-ready, observable, and reusable within the team.Contribute to trusted ingestion & enrichment foundations (Data Lake and Data as a Product):Build and maintain components of Preply's data lake.
Ensure every dataset has clear ownership, purpose, schemas, and quality expectations from first ingestion through downstream consumption by analytics, product, and ML teams.
Balance performance, cost, and reliability as the platform scales.Data quality, contracts & early validation:Implement data contracts between producers and consumers, covering schema, freshness, volume, and quality guarantees.
Embed validation, anomaly detection, and quality checks early in the ingestion lifecycle to catch issues before they propagate.
Apply standardized quality metrics.Build enrichment logic that joins, standardizes, and contextualizes data across domains usin

📌 Senior Engineer, Data Engineering (Barcelona)
🏢 Preply
📍 Barcelona