Lucky Cart Data Ops recruitment: 6 tech roles filled since 2021

About Lucky Cart

Lucky Cart is a French MarTech, founded in 2011 and headquartered in the heart of Paris.

Thanks to its proprietary technologies, the company leverages receipt-level data to deliver an ultra-personalized shopping experience to retailers, powered by Artificial Intelligence and Big Data.

Its team brings together experts in data science, machine learning, and AI, alongside retail specialists. Together, they combine their expertise to support a constantly evolving sector and tackle its business challenges.

🔗 Lucky Cart

Roles filled

We've been working with Lucky Cart since 2021 and have supported 6 hires:

• 2 Full-Stack developers
• 2 Product Managers
• 1 Lead Analytics Engineer
• 1 Data Ops

Our latest hire: the Data Ops

For this hire, we worked directly with Thomas Dunand, Lead DevOps, who already managed 2 DevOps and was hiring his team's first Data Ops.

Why this hire?

• Following a 2024 cost audit, a clear need emerged:
• → Bring in an expert capable of optimizing cost management tied to data volume.

The profile we were looking for

• Dual skill set: DevOps & Data FinOps.
• Hands-on mastery of BigQuery, DBT, Airflow to address FinOps topics.
• Ops skills, to bridge with the DevOps team.
• Key soft skills: pedagogy and the ability to evangelize teams on FinOps issues.

Recruitment challenges

✅ Find a profile that's technical and data-oriented, capable of understanding the Data Engineers' environment while having an Ops approach to interact with the Infra team.

✅ Identify a FinOps expert capable of optimizing cost management tied to data volume (storage, transfers…).

✅ A high-stakes goal: hire an operational profile already experienced in this kind of environment.

The secret to this hire?

🎯 Persistence: a process that lasted a month and a half with several challenges:

• Many candidates who fit on paper but didn't pan out in interviews.
• Competition with other agencies working on the same search.
• A very narrow market for these specific skills.
• Few technical Data Ops profiles, and few Data Engineers willing to transition into this kind of role.
• Rare are those with dual theoretical and practical expertise in FinOps.

💡 A demanding hire, but a successful one! 🚀

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