Data Engineer

🕒 il y a 1 mois

🇺🇸 États-Unis – Télétravail

💵 $95 000 - $140 000 / an

⏰ Temps Plein

🟢 Junior

🟡 Intermédiaire

🚰 Ingénieur Data

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MeridianLink

Site WebLinkedInTous les Emplois

501 - 1000 employés

Fondée en 1998

💳 Fintech

🏦 Banque

☁️ SaaS

💰 €485 000 000 Post-IPO Debt en 2021-11

Fintech • Banking • SaaS

MeridianLink est une entreprise de logiciels qui propose une plateforme cloud de prêt numérique et d'ouverture de compte de bout en bout pour les institutions financières. Sa plateforme configurable MeridianLink One inclut la gestion des prêts (consommation, non garanti, automobile, hypothécaire), l'ouverture de compte numérique, le financement sur le point de vente, les recouvrements, les données & rapports, et des services de conseil/analyse pour aider les banques et les coopératives de crédit à automatiser les processus, accélérer les décisions et améliorer les expériences client numériques. MeridianLink sert principalement les banques, les coopératives de crédit et les prêteurs hypothécaires à travers des solutions SaaS et un écosystème de partenaires.

Description

• Design, develop, and maintain scalable data pipelines and data products for internal and external consumers. • Build and optimize batch and near real-time data ingestion, transformation, and delivery processes. • Integrate data from internal and external sources to support business, reporting, and analytics requirements. • Collaborate with data architects, analysts, data scientists, and business stakeholders to deliver scalable data solutions and support Sisense dashboards and analytics assets. • Design and implement data models that support reporting, analytics, and operational use cases. • Ensure data quality, reliability, and performance through monitoring, validation, automated testing, and troubleshooting. • Write maintainable, well-documented, and testable code; participate in code reviews; and leverage AI-assisted development tools to improve quality and efficiency. • Support CI/CD, infrastructure automation, technical documentation, and continuous improvements to data architecture, tooling, and engineering practices

🎯 Exigences

• 2–4 years of professional experience in Data Engineering, Data Warehousing, or related roles. • Strong hands-on experience with Python and SQL for building scalable data pipelines and transformation logic. • Experience with Apache Spark, Parquet, and Azure Databricks, including Databricks workflows, Delta Lake, Delta Sharing, and Unity Catalog. • Strong SQL expertise including performance tuning, indexing, partitioning, query optimization, and stored procedure development. • Solid understanding of ETL/ELT methodologies, data warehousing principles, and modern data engineering best practices. • Experience designing and implementing data models to support analytics, reporting, and operational use cases. • Experience supporting or working with BI tools such as Sisense (or similar platforms). • Experience with CI/CD pipelines and version control practices (e.g., GitLab, Jenkins, or equivalent). • Experience working in fast-paced product environments with an emphasis on delivery, maintainability, and minimizing technical debt. • Strong communication skills with the ability to collaborate across technical and non-technical stakeholders

🏖️ Avantages

• Insurance coverage (medical, dental, vision, life, and disability) • Flexible paid time off • Paid holidays • 401(k) plan with company match • Remote work