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