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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Engineer - **Company:** Vibe - **Location:** Paris, France - **Experience:** Expert - **Salary:** €90,000.0 - €120,000.0 - **Contract:** Permanent contract - **Skills:** Airflow, Big Data, BigQuery, Cloud Computing, Data Infrastructure, Machine Learning, Automation of Marketing, Operational Databases, Data Streaming, Apache Spark, Druid, Apache Flink, Apache Kafka, Vertica - **Published:** July 2, 2026 - **Apply:** https://fr.indeed.com/viewjob?jk=85226efae61bba59 ## About the Role * 5+ years building and operating production data platforms at real volume, not analytics or BI-adjacent work. * Deep lakehouse experience across storage (Iceberg, Delta, or Hudi) and compute (Spark, DuckDB, or Trino) * Production experience with a modern orchestrator (Dagster, Airflow, or Prefect) plus dbt or an equivalent transformation framework * A proven track record of handling large volumes of data under time and cost constraints. * Operational ownership: on-call, incident response, alerts and runbooks you actually wrote * Cross-functional communication: you adapt detail to the audience and push back on stakeholders constructively, * A column-store analytics engine in production: ClickHouse ideally, or Druid, Pinot, or BigQuery at serious scale * Batch and streaming together: Kafka, Kinesis, or Flink feeding a serving layer, not just nightly batch * The exact stack: Dagster, Spark, DuckDB, Iceberg, ClickHouse Cloud, Cube.js. Any two or three is already strong * Streaming TV advertising or programmatic background, or experience with compliance-related problems ## Description Data isn't a support function at Vibe. It's the machinery. Every decision (which ad, which household, which moment) runs on it. You'll join the Data Platform team, which owns the company's entire data backbone: the storage layer holding several petabytes, the batch systems that feed Product, Sales, Finance, and ML, the real-time streams behind spend tracking and retargeting, and the ClickHouse and Cube reporting stack that serves sub-second analytics to advertisers inside the Clear platform. This role exists because we have real scaling problems (500k+ messages per second, petabytes stored, both growing) and we need engineers who can build the infrastructure to stay ahead of them. Three reasons to want this: you'll own projects end-to-end, from stakeholder requirements through schema, build, monitoring, and iteration; you'll work on genuine big-data scaling problems, not maintenance; and you'll have direct, measurable impact on the business, because here data is a first-class citizen. What You'll Do * Ship and operate production pipelines across batch, streaming, and reporting stacks, from requirements to monitoring * Design storage and compute for petabyte-scale datasets using Iceberg, Spark, DuckDB, and Trino * Cut cost and latency on specific pipelines and queries, with quantified, instrumented impact * Own the data contract for the ClickHouse and Cube reporting stack behind the Clear UI * Build alerts, SLOs, and runbooks so fewer incidents reach users * Lead incident response and carry on-call across production systems * Influence upstream producers on schemas, semantics, and SLAs for bid, win, and impression events * Build tooling, conventions, and data contracts that make the whole team faster, At Vibe, we run on three values: Impact, Ambition, and Urgency. We tie every goal to a real business outcome, think 10x rather than settling for good enough, and move daily rather than waiting for perfect conditions. You'll thrive here if you own outcomes without needing direction, default to action, and hold yourself to results, not effort. This is a high-performance environment with high-performance rewards: you'll work alongside people who push you, with real ownership over hard problems in a market that's moving fast. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Modern Data Architectures need Software Engineering](https://www.wearedevelopers.com/videos/1030-modern-data-architectures-need-software-engineering) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) ## Related Articles - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Dev Digest 139 - Soft and hard queries](https://www.wearedevelopers.com/magazine/487-dev-digest-139-soft-and-hard-queries) - [Dev Digest 193: Vibe Coding Honeymoon, NaN and the End of Interviews](https://www.wearedevelopers.com/magazine/652-dev-digest-193-vibe-coding-honeymoon-nan-and-the-end-of-interviews)