Postuler

Publié il y a 21 jours

Senior DataOps/Cloud Data Engineer

@ modis

Toronto, Ontario

ContratTemporaire8+ ans d’expérience
Postuler
SIGNAUX

En bref

Akkodis is hiring a Senior DataOps/Cloud Data Engineer on a 6-month B2B contract for a public sector client in Toronto. The role designs, builds and optimizes enterprise data pipelines, lakehouse platforms and CI/CD-enabled DataOps processes on Azure, Databricks and Oracle. The posting requires security clearance and onsite work 7.25 hours per day, Monday to Friday.

Responsabilités :

  • Design and optimize enterprise data pipelines and ETL/ELT solutions
  • Build cloud data lakehouse platforms on Databricks and Azure
  • Design data migration and integration across Oracle, Azure Data Lake, Databricks and Microsoft Fabric
  • Develop DataOps processes, CI/CD pipelines and deployment automation

Résumé des exigences :

  • 8+ years enterprise data engineering and cloud data platform experience
  • Databricks, Delta Live Tables or equivalent ETL/ELT experience
  • Advanced SQL including PL/SQL and T-SQL
  • Relational and dimensional data modelling expertise
  • Azure Data Factory pipeline experience
  • Security clearance required

Outils et compétences

Source et dates

Site carrière / système de candidatures · careerpage

Date publiée par l’employeur
2026-10-16
Première détection par notre source
2026-10-16
Mise à jour du dossier source
2026-10-16

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

Détails du poste

NiveauSenior
DomaineDéveloppement logiciel
Expérience8 an(s) et plus
Heures par semaine36.25
Horairejour
Déplacementsavion : aucun · route : aucun
Milieu de travailBureau
PositionSurtout assis
Exigences physiquesphysique faible · ordinateur élevé
Cote de sécuritéAutre cote

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

ChampValeur
Offres sur Jobsy94
Description

Position: Senior DataOps/Cloud Data Engineer

Duration: 6 Months assignment (contract)
Client Location: Toronto (Onsite: 7.25 hours/day between 8:00 AM and 5:00 PM, Monday to Friday)
Engagement Model: Professional Services Engagement – B2B (Incorporated Entities Only)

Note on Assignment Type

This position is provisionally Onsite, requiring 7.25 hours per calendar day between 8:00 AM and 5:00 PM, Monday to Friday (excluding breaks). Conditions may change based on organizational requirements and at the discretion of the Hiring Manager.

About the Engagement

Akkodis is seeking an experienced Senior DataOps/Cloud Data Engineer to support the design, development, modernization, and optimization of enterprise cloud data platforms and large-scale data integration solutions within a complex public sector environment.

The successful consultant will play a critical role in designing and implementing scalable data pipelines, data lakehouse architectures, cloud migration initiatives, and DataOps capabilities using modern Azure-based technologies. This role requires strong expertise in Databricks, Azure Data Factory, enterprise database technologies, cloud data engineering, automation, and data platform modernization.

Scope

  • Design, develop, automate, and optimize enterprise data pipelines and ETL/ELT solutions.

  • Build and maintain cloud-based data lakehouse platforms utilizing Databricks and Azure services.

  • Design and implement data migration and integration solutions across Oracle, Azure Data Lake, Databricks, and Microsoft Fabric platforms.

  • Develop scalable DataOps processes, CI/CD pipelines, and deployment automation frameworks.

Assignment Deliverables

  • Enterprise-grade ETL/ELT pipelines using Databricks, Delta Live Tables (DLT), and Azure Data Factory.

  • Unified data platform solutions leveraging Databricks Unity Catalog and Lakehouse architecture.

  • Data migration and integration solutions across multiple enterprise platforms.

  • Cloud-native data lake, data warehouse, and data lakehouse implementations.

  • CI/CD-enabled deployment pipelines integrated with Azure DevOps and Git repositories.

Expertise Required

Must Have:

  • 8+ years of experience designing and implementing enterprise data engineering and cloud data platform solutions.

  • Experience designing, building, automating, and optimizing complex ETL/ELT processes using Databricks, Delta Live Tables (DLT), or equivalent technologies.

  • Experience developing unified data platforms utilizing Databricks and Unity Catalog or equivalent technologies.

  • Strong experience with relational database technologies including Oracle, MySQL, and SQL Server.

  • Advanced knowledge of relational and dimensional data modelling concepts.

  • Advanced SQL expertise including PL/SQL and T-SQL development.

  • Strong hands-on experience with PySpark and big data processing frameworks.

  • Experience creating Azure Data Factory pipelines for data ingestion, orchestration, and transformation.

Nice to Have:

  • Experience with scripting and automation using Python, Scala, and Unix Shell Scripting.

  • Experience supporting large-scale OLTP and OLAP migration initiatives.

  • Experience managing cloud storage services, repositories, Key Vaults, virtual machines, and cloud infrastructure components.

Security Clearance

Required.

Important

This is a business-to-business engagement. Candidates must represent an incorporated entity, hold a valid business number, maintain appropriate insurance, and invoice for services rendered.

How to Apply

Submit your resume in confidence via the Akkodis Canada website.

We thank all applicants for their interest in this opportunity. Only candidates meeting the above qualifications will be contacted for further discussions.

Accessibility:

At Akkodis, part of The Adecco Group, our purpose is simple: to make the future work for everyone. We live our values, Passion, Collaboration, Inclusion, Courage, and Customers at Heart, by fostering a workplace where diversity is celebrated and every voice matter. We encourage applications from individuals of all backgrounds and identities. Together, we’re making the future work for everyone.



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