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Publié il y a 3 jours

Data Engineer

@ VySystems

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Toronto, Ontario

Temps plein4+ ans d’expérience
Postuler
SIGNAUX

En bref

VySystems is hiring a full-time Data Engineer to design, build and maintain scalable data pipelines for large financial datasets. The role requires at least 4 years of data engineering experience with advanced SQL and Python, plus hands-on work with Snowflake, Spark and Azure.

Responsabilités :

  • Design, build and maintain scalable data pipelines
  • Implement data architectures for large financial datasets
  • Write high-quality Python and SQL code
  • Integrate data governance and lineage tracking

Résumé des exigences :

  • 4+ years of data engineering experience
  • Advanced SQL and relational and NoSQL databases
  • Strong experience with Snowflake, Hadoop, Spark, Databricks, Azure
  • Proficiency in Python
  • Familiarity with orchestration tools

Outils et compétences

SnowflakeHadoopSparkPySparkDatabricksAzurePythonSQL
Source et dates

Type de source non vérifié · apify-linkedin

Date publiée par l’employeur
2026-11-10
Première détection par notre source
2026-11-14
Mise à jour du dossier source
2026-11-14

Ces dates décrivent le dossier source, pas une vérification en direct du recrutement. Consultez l’offre originale.

Détails du poste

NiveauIntermédiaire
DomaineDéveloppement logiciel
Expérience4 an(s) et plus
Heures par semaine40 (estimé)
Milieu de travailBureau
PositionSurtout assis
Exigences physiquesphysique faible · ordinateur élevé

Résumé et détails rédigés par l’IA à partir de l’offre; l’offre de l’employeur fait foi.

Postuler
ChampValeur
Offres sur Jobsy6
Description

Skills & Qualifications:

•4+ years of Data Engineering experience

•Advanced SQL; experience with relational and NoSQL databases

•Strong experience with Snowflake, Hadoop, Spark, PySpark, Databricks, Azure

•Proficiency in Python for data engineering

•Familiarity with orchestration tools and workflow management systems

Responsibilities:

•Design, build, and maintain scalable data pipelines using Snowflake, Hadoop, Spark, PySpark, Azure

•Implement data architectures and optimize workflows for large financial datasets

•Write high-quality, maintainable Python and SQL code following best practices

•Integrate data governance, metadata management, and lineage tracking into solutions

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