Founded in 2013 Voodoo is a tech company that creates mobile games and apps with a mission to entertain the world. Gathering 800 employees 7 billion downloads and over 200 million active users Voodoo is the #3 mobile publisher worldwide in terms of downloads after Google and Meta. Our portfolio includes charttopping games like Mob Control and Block Jam alongside popular apps such as BeReal and Wizz.
Team
The Engineering & Data team builds innovative tech products and platforms to support the impressive growth of their gaming and consumer apps which allow Voodoo to stay at the forefront of the mobile industry.
Within the Data team youll join the AdNetwork Team which is an autonomous squad of around 30 people. The team is composed of toptier software engineers infrastructure engineers data engineers mobile engineers and data scientists (among which 3 Kaggle Masters). The goal of this team is to provide a way for Voodoo to monetize our inventory directly with advertising partners and relies on advanced technological solutions to optimize advertising in a realtime bidding environment. It is a strategic topic with significant impact on the business.
This role can be done fully remote in any EMEA country.
Role
Design implement and optimize realtime data pipelines handling billions of events per day with strict SLAs.
Architect data flows for bidstream data auction logs impression tracking and user behavior data.
Build scalable and reliable event ingestion and processing systems using Kafka Flink Spark Structured Streaming or similar technologies.
Operate data infrastructure on Kubernetes managing deployments autoscaling resource limits and high availability.
Collaborate with backend to integrate OpenRTB signals into our data platform in near realtime.
Ensure highthroughput lowlatency processing and system resilience in our streaming infrastructure.
Design and manage event schemas (Avro Protobuf) schema evolution strategies and metadata tracking.
Implement observability alerting and performance monitoring for critical data services.
Contribute to decisions on data modeling and data retention strategies for realtime use cases.
Mentor other engineers and advocate for best practices in streaming architecture reliability and performance.
Continuously evaluate new tools trends and techniques to evolve our modern streaming stack.
Profile (Must have)
Extensive experience in data or backend engineering with at least 2 years building realtime data pipelines.
Proficiency with stream processing frameworks like Flink Spark Structured Streaming Beam or similar.
Strong programming experience in Java Scala or Python with a focus on distributed systems.
Deep understanding of event streaming and messaging platforms such as GCP Pub/Sub AWS Kinesis Apache Pulsar or Kafka including performance tuning delivery guarantees and schema management.
Solid experience operating data services in Kubernetes including Helm resource tuning and service discovery.
Experience with Protobuf/Avro and best practices around schema evolution in streaming environments.
Familiarity with CI/CD workflows and infrastructureascode (e.g. Terraform ArgoCD CircleCI).
Strong debugging skills and a bias for building reliable selfhealing systems.
Nice to have:
Knowledge of streamnative analytics platforms (e.g. Druid ClickHouse Pinot).
Understanding of frequency capping fraud detection and pacing algorithms.
Exposure to service mesh autoscaling and cost optimization in containerized environments.
Contributions to opensource streaming or infra projects.
Nice to Have
Knowledge of streamnative analytics platforms (e.g. Druid ClickHouse Pinot).
Understanding of frequency capping fraud detection and pacing algorithms.
Exposure to service mesh autoscaling and cost optimization in containerized environments.
Contributions to opensource streaming or infra projects.
Benefits
Bestinclass compensation
Other benefits according to the country you reside in
Disclaimer: Drjobpro.com is only a platform that connects job seekers and employers. Applicants are advised to conduct their own independent research into the credentials of the prospective employer.We always make certain that our clients do not endorse any request for money payments, thus we advise against sharing any personal or bank-related information with any third party. If you suspect fraud or malpractice, please contact us via contact us page.