Publié il y a 4 mois
Databricks Data Engineer
@ Querentia Inc.
Télétravail au Canada
En bref
Querentia Inc. is hiring a contract Databricks Data Engineer to build and manage scalable data pipelines and ETL/ELT workflows. The work involves Apache Spark, Python and SQL on cloud platforms (Azure, AWS or GCP).
Responsabilités :
- Design and manage scalable data pipelines using Databricks
- Build and optimize ETL/ELT workflows
- Process and analyze data with Apache Spark, Python and SQL
- Ensure data quality and pipeline performance
- Support cloud data engineering across Azure, AWS or GCP
Résumé des exigences :
- Strong hands-on experience with Databricks
- Proficiency in Apache Spark, Python and SQL
- Experience designing and maintaining ETL/ELT pipelines
- Knowledge of Azure, AWS or GCP
- Strong data integration and optimization skills
Outils et compétences
Source et dates
Type de source non vérifié · jsonld
- Date publiée par l’employeur
- 2026-07-09
- Première détection par notre source
- 2026-10-26
- Mise à jour du dossier source
- 2026-11-02
Ces dates décrivent le dossier source, pas une vérification en direct du recrutement. Consultez l’offre originale.
Détails du poste
| Domaine | TI |
| Milieu de travail | Bureau |
| Position | Surtout assis |
| Exigences physiques | physique faible · ordinateur élevé |
Résumé et détails rédigés par l’IA à partir de l’offre; l’offre de l’employeur fait foi.
Querentia Inc.
| Champ | Valeur |
|---|---|
| Offres sur Jobsy | 331 |
Job Summary
We are seeking a hands-on Databricks Data Engineer with experience building scalable data pipelines and supporting cloud-based data engineering initiatives. The ideal candidate will have strong expertise in Databricks, Apache Spark, Python, and SQL , with experience developing ETL/ELT workflows across cloud platforms.
Key Responsibilities
• Design, develop, and manage scalable data pipelines using Databricks .
• Build and optimize ETL/ELT workflows for data ingestion, transformation, and integration.
• Utilize Apache Spark, Python, and SQL for data processing and analytics.
• Collaborate with data engineers, analysts, and business stakeholders to deliver reliable data solutions.
• Ensure data quality, performance optimization, and efficient pipeline execution.
• Support cloud-based data engineering initiatives across Azure, AWS, or GCP environments.
Required Skills & Experience
• Strong hands-on experience with Databricks .
• Proficiency in Apache Spark, Python, and SQL .
• Experience designing and maintaining ETL/ELT pipelines.
• Knowledge of cloud platforms such as Azure, AWS, or GCP .
• Strong understanding of data integration, transformation, and performance optimization.
• Excellent analytical, problem-solving, and collaboration skills.
Preferred Skills
• Experience working in modern cloud data platforms and analytics environments.
• Familiarity with data governance and best practices for scalable data engineering solutions
Journal
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