Senior Data Engineer

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Vytwo Technologies Inc

Site WebLinkedInTous les Emplois

201 - 500 employés

Fondée en 2003

💼 Conseil

📦 Logistique

🎯 Recrutement

Consulting • Logistics • Recruitment

<Vytwo Technologies Inc. > Vytwo Technologies est un intégrateur d'applications d'entreprise et une société de services IT reconnue à l'échelle mondiale, basée à Minneapolis, MN. L'entreprise offre des services de conseil en informatique, d'intégration de systèmes, de développement d'applications et de produits sur mesure, de solutions liées à l'ERP et au cloud, de réingénierie, de maintenance et de services d'externalisation pour les organisations de taille moyenne à grande. Elle propose également des services de support produit, d'externalisation d'impression et de recrutement, mettant l'accent sur l'amélioration de l'efficacité des ventes des clients et l'accélération du temps de mise sur le marché grâce à une exécution disciplinée et axée sur les processus.

Description

• Design, develop, and maintain scalable data pipelines using Python, PySpark, and other modern programming languages to support both batch and streaming workloads • Build and optimize data processing frameworks on cloud platforms such as Databricks or Snowflake, ensuring performance, reliability, and cost efficiency • Design and implement robust data models, including transactional (OLTP) and dimensional (OLAP) schemas, to support analytics, reporting, and application integration • Develop high quality SQL code including complex queries, stored procedures, and views, with a focus on performance tuning and efficient data access patterns • Create and manage workflow orchestration using Apache Airflow or similar tools, ensuring reliable scheduling, dependency management, and monitoring • Implement and enforce data governance and metadata standards through tools such as Microsoft Purview, including data lineage, classification, cataloging, and security policies • Build automated data quality and validation frameworks to ensure accuracy, completeness, and reliability of production datasets • Collaborate with cross functional teams including data architects, analysts, scientists, and business stakeholders to understand requirements and deliver scalable, well designed data solutions • Lead technical design sessions and code reviews, promoting engineering best practices, reusability, and maintainability • Support cloud infrastructure and DevOps practices, including CI/CD pipelines, version control, testing automation, and environment management • Monitor and troubleshoot production data pipelines, proactively addressing issues, performance bottlenecks, and system failures • Contribute to the evolution of the enterprise data platform, recommending tools, frameworks, and architectures to improve scalability and efficiency

🎯 Exigences

• 7+ years of experience in data engineering, software engineering, or similar disciplines • Hands-on experience with Databricks or Snowflake • Experience with orchestration tools such as Apache Airflow • Experience working with cloud ecosystems (Azure preferred; AWS/GCP acceptable) • Advanced SQL skills and experience with OLTP and OLAP data modeling • Solid understanding of modern data warehousing, data lake, and ELT/ETL design patterns • Familiarity with data governance tools, especially Microsoft Purview • Solid programming expertise in Python, PySpark, or similar languages