Staff Data Engineer

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Payabli

Site WebLinkedInTous les Emplois

11 - 50 employés

Fondée en 2020

💼 Conseil

📣 Marketing

📦 Logistique

💰 €35 999 907 Series B - Payabli en 2025-06

Consulting • Marketing • Logistics

Payabli est une entreprise d'infrastructure de paiements de nouvelle génération qui permet aux plateformes logicielles d'intégrer, de gérer et de monétiser les paiements. Elle propose une gamme complète de capacités — Pay In (acceptation des paiements et intégration des commerçants), Pay Out (comptes payables et paiements aux fournisseurs/partenaires), et Pay Ops (opérations, risques, facturation et rapports) — livrée via des API, des composants intégrables et des services de conseil personnalisés. Payabli cible les entreprises SaaS, les institutions financières, les services technologiques et les grands commerçants, et est un facilitateur de paiements/enregistreur ISO offrant des solutions de paiements conformes et évolutives et des outils d'intégration adaptés aux développeurs.

Description

• Architect the platform. Set our warehouse/lakehouse direction and stand up the data lake and layered architecture that turns our raw system of record into trustworthy, queryable, intelligence-ready data. • Build the pipelines. Design and run batch and streaming pipelines that move data reliably out of our production systems - CDC, ELT, and real-time where it matters. • Model the data. Define the canonical datasets and models the whole company depends on, getting the grain, semantics, and contracts right. • Own reliability and accuracy. This is financial data, so correctness is non-negotiable. You'll own data quality, observability, integrity checks, and the testing and monitoring that let us trust it. • Build for a regulated environment. Design in role-based access, masking, lineage, and auditability from day one, and keep sensitive financial data out of places it doesn't belong. • Enable AI/ML and analytics. Build the feature pipelines and trustworthy data foundation our intelligence work relies on, moving us from systems of record toward systems of intelligence and action. • Set the standard. Establish the practices, tooling, and CI/CD for data that the future team inherits. You're setting the bar, not just clearing it.

🎯 Exigences

• 8+ years building production data systems, with a track record of owning architecture and seeing big decisions through to production. • Expert SQL and strong Python. • Deep experience in at least one modern lakehouse/warehouse ecosystem - for example Snowflake with dbt and Fivetran, or Databricks with Spark, Delta Lake, and Unity Catalog. We care that you've gone deep somewhere and can reason from first principles across stacks, not that you've used a specific product. • Strong data modeling skills - dimensional, normalized, or Data Vault - and a sense for designing models that age well. • Experience with pipeline orchestration (Airflow, Dagster, Prefect, or equivalent) and large-scale processing (such as Spark). • Production experience on a major cloud (AWS, GCP, or Azure), including security and cost patterns. • Experience working with sensitive or regulated data - access controls, encryption, governance, and an instinct for keeping the blast radius of mistakes small. • A high technical bar set through influence and example. You make the work and the people around you better, and you're as comfortable in the codebase as you are in a design review.

🏖️ Avantages

• Competitive salary • Stock options with the potential to unlock more equity as we grow • Flexible PTO and paid parental leave • Medical, dental, & vision insurance • 401K, HSA, pre-tax savings programs