Senior Data Engineer – Feature Platform

Voodoo

Senior Data Engineer managing the foundational infrastructure for ML Ads at Voodoo. Focusing on batch and real-time data processing to enhance machine learning capabilities.

Posted 5/4/2026full-timeParis • 🇫🇷 FranceSeniorWebsite

Tech Stack

Tools & technologies

AWSAzureCloudETLGoGoogle Cloud PlatformJavaPythonSpark

About the role

Key responsibilities & impact

Take end-to-end ownership of highly visible projects from initial ideation to production release.
Actively partner across the entire data lifecycle to discover high-impact feature opportunities.
Collaborate closely with Data Scientists and ML Engineers to design, scale, and optimize core components.
Build, maintain, and optimize mission-critical data pipelines spanning both extensive batch processing and continuous real-time streams.
Actively build and maintain the high-load backend applications that power our ML model serving.
Work hand-in-hand with our infrastructure teams to guarantee the reliability, security, and immense scalability required for an ad-network ecosystem.
Thrive in a fast-paced agile environment with rapid decision-making processes.
Actively contribute to our engineering culture, share knowledge, and ensure every team member feels comfortable, supported, and empowered to grow in their role.

Requirements

What you’ll need

6+ years of proven experience as a Data Engineer, ML Engineer, Backend Engineer, or a closely related role in a high-scale environment.
Big Data & Streaming Mastery: Extensive hands-on experience working with Flink or Spark at scale.
Coding Proficiency: Advanced expertise in Python for robust ETL pipelines and custom feature-definition SDKs/DSLs
Experience or a strong willingness to work with Golang for building high-performance, low-latency backend applications as well as familiarity with Java is highly valued for our Flink streaming workloads.
Data Architecture: Deep understanding of modern Data Lakehouse design principles, open table formats (like Iceberg), optimization techniques, and data modeling.
Cloud & DevOps: Strong hands-on experience with a major cloud platform (AWS, GCP, Azure, etc.), though AWS is our preferred environment.
ML Production Awareness: You have a solid grasp of the unique challenges involved in running ML models in production, including working with Feature Stores, mitigating training-serving skew, and model monitoring.
System Design: You are highly familiar with topics surrounding system scalability, high availability/reliability, low-latency API design, and security best practices.

Benefits

Comp & perks

Swile Lunch voucher
Gymlib (100% covered by Voodoo)
Premium healthcare coverage with SideCare, 100% covered for you and your family
Wellness activities in our Paris office
Remote Fridays

ATS Keywords

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Hard Skills & Tools

Data EngineeringMachine Learning EngineeringBackend EngineeringBig DataStreamingPythonGolangJavaData ArchitectureCloud Computing

Soft Skills

CollaborationOwnershipAgilityKnowledge SharingSupportive Environment