Senior DataOps/Cloud Data Engineer
- Toronto, ON, Canada
Contract · Temporary
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Job details
- Job type
- Contract · Temporary
- Apply by
- Experience
- 8+ years of experience designing and implementing enterprise data engineering and cloud data platform solutions.
- Posting language
- English
- Posted
Original job 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.
More about this job
Responsibilities
The Senior DataOps/Cloud Data Engineer at Akkodis will build and automate data pipelines, design cloud data lakehouse platforms, and migrate and integrate data across enterprise systems. The role also sets up deployment automation and CI/CD pipelines for the data platform.
Requirements
Candidates need 8+ years of enterprise data engineering and cloud data platform experience, including Databricks, Delta Live Tables, Azure Data Factory and PySpark. They also need advanced SQL (PL/SQL and T-SQL), relational and dimensional data modelling, and required security clearance.
Skills
- Databricks
- Delta Live Tables (DLT)
- Azure Data Factory
- Unity Catalog
- Lakehouse architecture
- PySpark
- Apache Spark
- Oracle
- SQL Server
- MySQL
- PL/SQL
- T-SQL
- Relational data modelling
- Dimensional data modelling
- ETL/ELT development
- Azure Data Lake
- Microsoft Fabric
- Azure DevOps
- Git
- CI/CD
- Python
- Scala
- Unix shell scripting
- Azure Key Vault
- Cloud data migration
Categories
- Technology
- Data & Analytics
- Consulting
- Government & Public Sector
- Software
Keywords
- Databricks
- Delta Live Tables
- Azure Data Factory
- Unity Catalog
- Microsoft Fabric
- PySpark
- Azure Data Lake
- Oracle
- SQL Server
- MySQL
- PL/SQL
- T-SQL
- ETL
- ELT
- data pipelines
- data lakehouse
- DataOps
- CI/CD
- Azure DevOps
- data engineer
Seniority
Senior
Tools
- Databricks
- Azure Data Factory
- Oracle
- SQL Server
- MySQL
- Azure Data Lake
- Microsoft Fabric
- Azure DevOps
- Git
- Azure Key Vault