Senior Data Engineer

Emploi pas sur LinkedIn

🕒 il y a 5 jours

🌐 États-Unis, Canada – Distant

🇺🇸 États-Unis – Télétravail 🇨🇦 Canada – Télétravail

💵 $125 000 - $155 000 / an

⏰ Temps Plein

🟠 Senior

🚰 Ingénieur Data

Postuler Maintenant

Trouver des Emplois à Distance Similaires

Configurer une alerte email pour les nouveaux emplois

📊 Vérifiez votre score de CV pour ce poste

Améliorez vos chances d'obtenir un entretien en vérifiant votre score de CV avant de postuler.

Télécharger le CV

FutureFit AI

Site WebLinkedInTous les Emplois

11 - 50 employés

🤖 Intelligence artificielle

🤝 B2B

☁️ SaaS

💰 Seed Round en 2022-03

Artificial Intelligence • B2B • SaaS

FutureFit AI s'associe avec des entreprises du Fortune 500, des gouvernements et des organisations de développement de la main-d'œuvre pour fournir un outil alimenté par l'IA qui agit comme un GPS pour aider les travailleurs à naviguer dans les transitions de carrière, les soutenant depuis l'orientation professionnelle, jusqu'à la reconversion, en passant par le placement professionnel.

Description

• Design, build, and operate the ingestion and transformation pipelines that bring labor market, customer, and product data into our warehouse as well as into the product • Own how our core data is structured, tested, and documented, including the skills, occupation, and career taxonomies at the center of the product • Build the transformation layer and datasets that power internal analytics, Looker/Quicksight reporting, and the insights we deliver to customers • Build and maintain the pipelines that feed our matching and recommendation models, and partner with Engineering and Data Scientists to get models deployed, monitored, and improved in production.

🎯 Exigences

• Strong data engineering experience (roughly 4+ years) designing and operating production ETL/ELT pipelines that other people and systems depend on • Fluency in Python and SQL, with real depth in SQL — experience in modeling data in a warehouse/data lake, not simply querying it • Hands-on experience with a modern orchestration and transformation stack (Airflow, dbt, or close equivalents) and with cloud data warehouses • Experience integrating data from varied external sources — third-party data providers, APIs, flat file feeds — including handling schema changes, unreliable delivery, and inconsistent quality from upstream • Comfort working with large, messy, inconsistently structured data, and sound judgment about when to clean it, when to model around it, and when to push back on the source • A builder's instinct for reliability: testing, monitoring, and debugging your own pipelines rather than waiting for someone to report the breakage • Clear communication: you can explain a data model and its tradeoffs to a non-technical audience.

🏖️ Avantages

• Competitive salary • Flexible work arrangements • Professional development opportunities • Travel for team gatherings and off-sites