Finance Data Engineer

Voodoo

~$57,512 - $106,808Market Estimate

Paris

Full-Time

Mid (3-6 yrs)

Engineering & Development

Posted on September 30, 2026

About Voodoo

Voodoo is a consumer tech company founded in Paris in 2013, with one mission: entertain the world. Today we are 1,000 people, generating $1b+ in annual revenue, profitably. Our games and apps have passed 7 billion downloads and reach 200 million+ active users every month, making Voodoo the #3 mobile publisher worldwide in downloads, after Google and Meta. We were backed by Goldman Sachs, Tencent and GBL along the way.

Team

Our Corporate teams support the company's performance and growth whilst putting people at the core of everything they do. As a French tech leader and global successful company, our Corporate teams are constantly looking for ways to innovate and increase organisation efficiency to keep Voodoo ahead of the market. Voodoo's Corporate function is composed of three teams: HR, Legal and Finance, working together to drive Voodoo's success.

As Voodoo continues to grow, we are transforming the way Finance uses data and technology. Our ambition is to move from fragmented, spreadsheet-heavy workflows to a modern, reliable, and increasingly automated Finance data platform.

Role

We're looking for a Finance Data Engineer to join our Corporate team. In this role, you'll own the technical transformation of Finance by building the data foundations, pipelines, and internal tools that enable Finance teams to operate more efficiently and make better decisions.

Reporting to the CFO, you will work closely with Finance stakeholders and Voodoo's central Data team, combining data engineering, business understanding, and product thinking to turn complex Finance needs into reliable and maintainable solutions.

Define and drive the roadmap for Finance data, automation, and internal tooling
Build and progressively scale Voodoo's Finance data platform, prioritising the use cases that create the greatest business value
Migrate critical data transformations and workflows from spreadsheets and legacy tools to tested, documented, code-based solutions
Create reliable data models and pipelines for Finance reporting, analysis, forecasting, and operational processes
Establish strong standards for data quality, observability, documentation, security, and access management
Partner closely with Accounting, FP&A, Controlling, Treasury, and other Finance stakeholders to translate their needs into scalable technical solutions
Collaborate regularly with Voodoo's Data leadership and engineering teams to align on architecture, tooling, and best practices
Build intuitive dashboards and internal applications that allow Finance teams to explore data and manage workflows independently
Identify AI and automation opportunities, take them from prototype to production, and measure the value they create
Help Finance teams adopt data and AI tools effectively through documentation, training, and day-to-day support

Profile

Significant experience in data engineering, analytics engineering, or a closely related role, including ownership of production-grade data solutions
Proven track record of building or substantially improving a modern data platform or analytics stack
Highly proficient in SQL and comfortable building production systems in Python
Strong software-engineering practices applied to data work: testing, version control, code review, documentation, and monitoring
Solid understanding of core corporate Finance and accounting concepts; familiarity with French accounting principles is a strong advantage
Ability to translate ambiguous business needs into clear, pragmatic technical solutions
Comfortable working autonomously, prioritising competing needs, and delivering value incrementally
Strong communication skills with both technical and non-technical stakeholders, in French and English
Curious about the evolving data and AI ecosystem — you test new approaches on real problems and form your own point of view
Rigorous, detail-oriented, and focused on measurable outcomes; pragmatic in technology choices, knowing when to build, adopt open-source, or buy commercial solutions

Nice to have:

Experience building tools or data products for Finance teams
Experience deploying AI agents or AI-enabled workflows into production
Familiarity with the mobile gaming, consumer apps, advertising, or digital analytics ecosystem
Experience operating data infrastructure on AWS