Data Observability Engineer
Criteo
Paris, France
il y a 4j

Who we are Criteo (NASDAQ : CRTO) is the global technology company powering the world’s marketers with trusted and impactful advertising.

2,800 Criteo team members partner with over 20,000 customers and thousands of publishers around the globe to deliver effective advertising across all channels, by applying advanced machine learning to unparalleled data sets.

Criteo empowers companies of all sizes with the technology they need to better know and serve their customers. Challenges of this role The Site Reliability teams keep one of the largest computing platforms in the AdTech world functioning like clockwork.

They are processing, storing and monitoring through large scale data compute & storage services (Hadoop, SQL & NoSQL), streaming (Kafka), platform as a service (Chef, Mesos), identity management (Kerberos) and analytics (Hive, Druid, Vertica).

The Data Group is in charge of hosting and producing the data for operations, reporting and machine learning purposes. We deliver can't-fail systems and services distributed across 9 data centers, spanning 3 continents and serving billions of Internet users.

This includes the systems that host the data, the pipelines responsible of producing the core data and the tools to monitor and understand the data life cycle.

The Data Observability team provides tools for monitoring, documenting and governing data. As part of this team you will : - Build and maintain the tools that help us managing the thousands of datasets, complex flows and large data producer and consumer bases : data discovery, cluster usage, data quality monitoring, lineage, etc.

  • Build and maintain our data documentation software providing our large base of data producers and consumers with the tool to understand, discover and collaborate on data - Understand large data sets that meet Analysts or Scientists requirements and help them build efficient models inside a sound data architecture - Participate in building the long term vision of optimal data systems
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