Azure Data Engineer

Role : Azure Data Engineer

Location : Toronto, ON (Hybrid - 3 days onsite)

Job type : Long-term Contract / Full-time opportunity

Experience : 5+ years

Job Description : We are looking for a highly skilled professional to design, build, and maintain scalable data solutions while ensuring data quality and driving data innovation.

Requirements

• Over 3 years of experience working with Azure Cloud Resources (ADLS, ADF, Dataflow).
• At least 2 years of hands-on experience with DBT(Must).
• Proficiency in advanced SQL, data integration, and data modeling principles.
• Experience with Python programming and Git for version control.
• Familiarity with DevOps practices for automation and deployment.
• Strong technical and problem-solving skills.

Responsibilities

Data Development & Integration : Design and build data solutions using Azure Cloud Resources (ADLS, ADF, Dataflow) in accordance with organizational standards to ensure resilience and scalability.

• Data Modeling & Metadata Management : Create, update, and maintain data models based on business needs and manage metadata repositories to ensure accurate and up-to-date information.
• ETL Processes & Data Preparation : Extract, transform, and load data from various sources, ensuring data quality, integrity, and convergence of datasets using DBT.
• Programming & Scripting : Develop scripts and programs using Python and employ Git for version control and code management.
• DevOps & Automation : Implement DevOps practices to automate workflows and ensure continuous integration and deployment.
• Problem Resolution & Advanced SQL : Use advanced SQL skills to resolve issues within databases, data products, and processes.

Qualifications

• Data Development & Integration : Design and build data solutions using Azure Cloud Resources (ADLS, ADF, Dataflow) in accordance with organizational standards to ensure resilience and scalability.
• Data Modeling & Metadata Management : Create, update, and maintain data models based on business needs and manage metadata repositories to ensure accurate and up-to-date information.
• ETL Processes & Data Preparation : Extract, transform, and load data from various sources, ensuring data quality, integrity, and convergence of datasets using DBT.
• Programming & Scripting : Develop scripts and programs using Python and employ Git for version control and code management.
• DevOps & Automation : Implement DevOps practices to automate workflows and ensure continuous integration and deployment.
• Problem Resolution & Advanced SQL : Use advanced SQL skills to resolve issues within databases, data products, and processes.

Warm Regards,

[email protected]

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