Data Engineer

🕒 il y a 5 mois

🐊 Florida – Distant

info

⏰ Temps Plein

🟡 Intermédiaire

🟠 Senior

🚰 Ingénieur Data

🦅 Parrain de Visa H1B

info

🗣️🇺🇸🇬🇧 Anglais requis

AWS

Cloud

ETL

NoSQL

Pandas

PySpark

Python

Spark

SQL

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Logo of Urban SDK

Urban SDK

11 - 50 employés

Fondée en 2018

💼 Conseil

📦 Logistique

🏥 Santé

💰 €977 498 Venture Round - Urban SDK en 2024-09

Consulting • Logistics • Healthcare

Urban SDK est une entreprise SaaS qui fournit des services d'IA géospatiale et d'analytique routière aux organisations du secteur public et aux agences de transport. Sa plateforme intègre des données de localisation et de trafic pour produire des analyses horaires de vitesse, des temps de retard de trajet, des volumes, des inventaires routiers et des risques de collision, permettant ainsi aux services de sécurité publique, aux services d'infrastructure, aux agences de transit et aux gestionnaires d'urgence de hiérarchiser les ressources, d'automatiser les flux de travail et de réagir plus rapidement aux événements de sécurité et de catastrophe.

Description

• Design, implement, and maintain scalable data pipelines and ETL/ELT workflows on Databricks and cloud platforms. • Manage large-scale geospatial and temporal datasets stored in AWS S3. • Collaborate with data scientists to productionize machine learning models and ensure smooth data availability. • Implement data validation, testing, and monitoring frameworks to ensure data accuracy, consistency, and reliability. • Optimize data storage and processing strategies to handle high volumes of traffic and mobility data efficiently. • Develop and maintain documentation for data workflows, architecture, and processes. • Work closely with cross-functional teams to understand data requirements and ensure timely delivery. • Stay up-to-date with the latest trends and best practices in data engineering, cloud technologies, and big data processing.

🎯 Exigences

• Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field. • 3+ years of experience as a data engineer or in a similar role. • Strong proficiency in Python and associated libraries for data engineering (pandas, PySpark, etc.). • Hands-on experience with Databricks and Spark for large-scale data processing. • Experience with AWS services, especially S3, and knowledge of cloud-based data architectures. • Solid understanding of data pipeline testing, version control, and CI/CD practices. • Experience with SQL and NoSQL databases. • Strong problem-solving skills and attention to detail.

🏖️ Avantages

• Annual Bonus • Medical, Vision, Dental • 401(k) • 21 Days Vacation • Office Lunch provided

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