Experienced Data Engineer - Platform

Paris

Full Time Mid-level / Intermediate EUR 69K - 129K * ^est.

Voodoo

We entertain the world with iconic apps and games.

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Posted 6 days ago

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 roles requires to be onsite 3 days/week and is Paris based.

Role

Build and maintain efficient ETL/ELT data pipelines using tools like DBT, Airflow, or similar orchestration systems.
Collaborate cross-functionally with data scientists, analytics teams, and product engineers to understand data needs and translate them into robust data solutions.
Support the development and maintenance of our Iceberg lakehouse.
Monitor data pipeline performance and resolve issues related to data quality, latency, and reliability.
Assist in developing and enforcing data governance, documentation, and security policies.
Participate in code reviews, testing, and deployment processes to ensure high engineering standards.
Contribute to automation and infrastructure improvements using IaC and CI/CD tools (e.g., Terraform, CircleCI).
Stay up to date with modern data engineering trends, tools, and best practices.

Profile (Must have)

3–5 years of experience in data engineering, software engineering.
Proficiency in Python, SQL, and data transformation tools.
Experience with data pipeline orchestration tools (e.g., Airflow, Prefect, Dagster).
Solid understanding of data warehousing concepts, distributed systems and cloud data platforms.
Knowledge of data modeling, data governance, and security best practices.
Strong problem-solving skills and attention to detail.
Excellent communication and collaboration abilities.

Nice to have

Experience working with streaming data technologies (e.g., Kafka, Spark Streaming, Kinesis).
Exposure to DBT or similar data transformation frameworks.
Knowledge of Infrastructure-as-Code and containerization (Terraform, Docker, Kubernetes).
Interest in observability, data lineage, and cataloging tools.