Senior Data Engineer - Central Data & Analytics Team
Voodoo is hiring a Senior Data Engineer - Central Data & Analytics Team in Paris, France. Level rates it ; you can apply on Voodoo.
Level's read on this job
- Level rates this data engineer role Works on AI ●●●○: the daily work is on AI products, without building the model.
- The posting allows some remote work.
- Tools and skills the posting cites include Claude, Claude Code and Codex.
- Level classifies it as a senior role.
- Level lists 103 other open roles at Voodoo.
AI in this role
Builds and operates robust data pipelines while integrating AI tooling and LLM-assisted features into the data platform.
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.
TeamThe Engineering & Data team builds innovative tech products and platforms to support the impressive growth of Voodoo's gaming and consumer apps, keeping us at the forefront of the mobile industry. The team plays a key role in Voodoo's long-term strategy: it accelerates product diversification and provides a state-of-the-art growth engine to distribute and scale our games. We create solutions that drive growth with a pragmatic approach, ranging from simple search to complex machine learning systems.
Within Engineering & Data, the Central Data & Analytics team makes data a reliable guide for the whole company. Data engineers, analytics engineers, data analysts and a product data PM work side by side to build and grow the foundations behind every critical business and product decision at Voodoo.
This position is hybrid and requires 3 days/week in our Paris office.
RoleWe’re looking for a Senior Data Engineer to join our Engineering & Data team. In this role, you’ll be responsible for a wide array of topics such as:
Build and operate robust data pipelines that keep pace with ever-evolving business needs, ensuring the architecture supports them cleanly.
Contribute to the codebase, ship and maintain your changes in production, and champion strong coding and data engineering practices.
Use AI coding tools (Claude Code, Codex, and whatever comes next) as a core part of your daily workflow — to move faster on pipelines, migrations, tests and documentation — while staying fully accountable for what you merge.
Look for opportunities to put AI inside our data platform, not just around it: LLM-assisted data quality checks, semantic layers, natural-language access to datasets, agent-driven internal tooling.
Take ownership of projects from initial discussions to release: feature estimation and scoping, architecture design, benchmarking of new technologies, product feedback.
Work in a very agile environment with a fast decision process.
Collaborate directly with back-end engineers, data scientists, mobile game and consumer app teams, product and marketing.
Extensive experience as a Data Engineer or in a similar role.
A proven track record of building and optimizing data pipelines for massive volumes of data (at scale).
Strong experience with scalability, reliability, and security topics.
Hands-on experience coding with AI assistants and agentic tools — you know how to give them the right context, break work down for them, and review their output critically rather than trusting it blindly.
Genuine curiosity about modern tooling and practices: you follow how the data and AI ecosystem is evolving, try new tools on real problems, and form your own opinion instead of following hype. You can explain why you adopted something — or why you dropped it.
Strong analytical skills and comfort working with unstructured datasets.
Experience with Amazon Web Services.
Result-oriented and focused on the value your work creates.
Curious about business needs and keen to build innovative, pragmatic solutions that grow the business through data.
Excellent communication skills (you can speak and write English).
Experience with LLM-based systems (RAG, evals, prompt and context engineering) is a strong plus.
Experience in gaming, advertising, or another fast-growing company is a plus.
Familiarity with Voodoo's ecosystem: gaming, apps, advertising, analytics.
Amazon Web Services; Python; Spark; Scala; Terraform; SQL (Athena, StarRocks); DBT;; Airflow; Kubernetes; AI-assisted development tooling (Claude Code, MCP-based internal tools)
Competitive salary based on experience
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
How we rate this
Senior Data Engineer - Central Data & Analytics Team at Voodoo rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in data engineer jobs at this level
Pay
- Typical data engineer job
- $146k
This posting doesn't list pay. Use the typical data engineer figure when pay comes up. See data engineer jobs
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- Tell me about a project where data engineering was part of your work. What did you do?
- Tell me about a project where etl was part of your work. What did you do?
- Tell me about a project where data pipelines was part of your work. What did you do?
- Tell me about a project where ai tooling was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: RAG, Data Engineering, ETL, Data Pipelines, and AI Tooling. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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