Teads Engineering Blog
Unit testing with dbt
Challenges encountered while migrating Redshift + Spark pipelines to our new dbt + BigQuery stack
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From Marketer to Developer at Teads: How Did I Make the Transition?
How did I come to leave my previous job in marketing and join Teads, an ad-tech company, as…
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Cross-cloud analytics workloads with BigQuery Omni and Looker
Teads’ Petabyte-scale data infrastructure is a critical component of its end-to-end advertising platform. In this talk at the…
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A Pragmatic Data Stack
Teads processes Terabytes of data every day with Stack Data that reflects our engineering culture: pragmatic. Like many…
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Moving from Pull to Push and dividing by 1000 the network traffic
Within Teads, the Buying Engine is the backend responsible for delivering thousands of Ad campaigns at all times…
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Future-proofing analytics event ingestion into Teads’ data warehouse
At Teads we are dealing with the processing of several billions of analytics events per hour. Those events…
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How we made our reporting engine 17x faster
In this article, we will see how we increased our reporting performance by moving most of our business…
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Takeaways of building a business-critical low-latency microservice at scale
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Zero Trust at Teads
How do we keep the Teads Platform and its data secure on a global scale?
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Our Engineering hiring process at Teads
Building a great interview process is quite tricky, there is no magic playbook for that. Here is some…
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Dynamic Cache Replication Using gRPC Streaming
How switching to a push architecture allowed decoupling a highly scaled process from our fixed-sized Cassandra cluster
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