Senior Data Engineer - Streaming Platform

-; Paris; À distance; EUR 50 000 - 90 000; Plein temps

Résumé du poste

Une entreprise innovante dans le secteur des jeux mobiles recherche un ingénieur en données talentueux pour rejoindre une équipe dynamique. Dans ce rôle, vous serez responsable de la conception et de l'optimisation de pipelines de données en temps réel, en utilisant des technologies avancées comme Kafka et Flink. Vous travaillerez sur des projets stratégiques qui ont un impact significatif sur les revenus publicitaires, tout en collaborant avec des ingénieurs de haut niveau. Si vous êtes passionné par les données et souhaitez faire partie d'une équipe qui façonne l'avenir du divertissement numérique, cette opportunité est faite pour vous.

Prestations

Meilleure rémunération

Autres avantages selon le pays de résidence

Qualifications

• Expérience en ingénierie des données ou backend, avec 2 ans d'expérience dans la construction de pipelines de données en temps réel.
• Compétences en traitement des flux avec des frameworks comme Flink ou Spark.

Responsabilités

• Concevoir et optimiser des pipelines de données en temps réel traitant des milliards d'événements par jour.
• Collaborer avec le backend pour intégrer les signaux OpenRTB dans notre plateforme de données.

Connaissances

Ingénierie des données

Traitement des flux en temps réel

Java

Scala

Python

Kubernetes

Kafka

Flink

Spark Structured Streaming

CI/CD

Outils

GCP Pub/Sub

AWS Kinesis

Apache Pulsar

Terraform

ArgoCD

CircleCI

Protobuf

Avro

Description du poste

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 chart-topping 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, you'll join the Ad-Network Team which is an autonomous squad of around 30 people. The team is composed of top-tier 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 real-time 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 real-time 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 real-time.
• Ensure high-throughput, low-latency 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 real-time 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 real-time 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 infrastructure-as-code (e.g., Terraform, ArgoCD, CircleCI).
• Strong debugging skills and a bias for building reliable, self-healing systems.
• Nice to have:
• Knowledge of stream-native analytics platforms (e.g., Druid, ClickHouse, Pinot).
• Understanding of frequency capping, fraud detection, and pacing algorithms.
• Exposure to service mesh, auto-scaling, and cost optimization in containerized environments.
• Contributions to open-source streaming or infra projects.

Nice to Have

• Knowledge of stream-native analytics platforms (e.g., Druid, ClickHouse, Pinot).
• Understanding of frequency capping, fraud detection, and pacing algorithms.
• Exposure to service mesh, auto-scaling, and cost optimization in containerized environments.
• Contributions to open-source streaming or infra projects.

Benefits

• Best-in-class compensation
• Other benefits according to the country you reside in