Data Engineer

  • Paris, France

Data Engineer

Job description

Adikteev is the leading app re-engagement platform for performance-driven marketers. We help the world’s top-spending app publishers increase retention, reacquire churned users and drive incremental revenue.

Our Main Engineering Challenges

  • Very high traffic environment with low latency constraints
  • An infinite source of Machine Learning use cases, ranging from ad performance, pricing prediction to ad delivery pacing and forecasting
  • Store, process and expose a big amount of data. Train and execute prediction jobs on it.
  • Large datasets that we need to compute in near real time (auction resolution) and even greater volumes for analytics use cases
  • observability, monitoring, alerting
  • Hold the scale (technical and business) and reduce technical debt

Your long-term Missions

  • Evaluate, deploy and maintain our data stores, processes and schedulers
  • Make the data available : processes, stores, aggregation, APIs development, …
  • Challenge past choices to support the data scale
  • Keep in touch with technology, propose innovative solutions
  • Industrialize, monitor and make Data Science Algorithms scale
  • Be part of a SCRUM team with other technical people and a product owner

Your short/mid-term Missions

  • Hold the data scale
  • Industrialize Data processes (test, monitoring, alerting, error recovery)
  • Replace Spark Streaming by another technology for some jobs
  • Migrate Spark jobs running on EMR in Kubernetes
  • Improve some data processes using Kafka



  • Must have :
    • Good interpersonal skills ; collaborative ; open-minded
    • Be able to explain your decision and share your knowledge
    • Strong problem solving skills
    • Spark ; Python ; distributed computing and storage ; well knowledge of at least 1 public cloud (AWS, Azure, GCP)
  • It’s a plus : expertise on AWS ; good knowledge of Scala ; software engineering culture ; data scale experience
  • Nice to have : Kafka ; Airflow ; Redis ; Cassandra ; Kubernetes


  • Data : Scala, Python, Spark, Airflow, Kafka, Redis, Cassandra, ...
  • Backend : Node.js, Go, Python, ...
  • Infra : Full AWS, Kubernetes, Ansible, Terraform, Docker