Data Engineer – Hybrid in Toronto

Data Engineer – Hybrid in Toronto

Toronto Full-Time 118000 - 145000 $ / year (est.) Hybrid
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At a Glance

  • Tasks: Design data transformation frameworks for analytics-ready datasets and support reporting processes.
  • Company: Global technology consulting firm based in downtown Toronto.
  • Benefits: Competitive salary, hybrid work model, and opportunities for professional growth.
  • Other info: Exciting opportunity to work in a collaborative environment.
  • Why this job: Join a dynamic team and make an impact on large-scale infrastructure programs.
  • Qualifications: Experience with SQL, Snowflake, and Azure Data Factory required.

The predicted salary is between 118000 - 145000 $ per year.

A global technology consulting firm in Toronto is seeking a Data Engineer to support large-scale infrastructure programs.

This role involves designing data transformation frameworks for analytics-ready datasets for Power BI reporting.

The ideal candidate will have extensive experience with SQL, Snowflake, and Azure Data Factory, and will work collaboratively to manage data ingestion and reporting processes.

Competitive salary range from $118,000 to $145,000 annually, with a hybrid work model at downtown Toronto. #J-18808-Ljbffr

Data Engineer – Hybrid in Toronto employer: Accenture

Accenture Consulting is an exceptional employer that fosters a dynamic and inclusive work culture, empowering employees to innovate and excel in their roles. With a strong focus on professional development, team collaboration, and leadership opportunities, you will thrive in a supportive environment while working on impactful payment solutions for clients across Canada and beyond. The company's commitment to diversity and global reach makes it a unique place to grow your career in the fast-evolving payments landscape.

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Contact Details:

Accenture Recruitment Team

We think you need these skills to ace Data Engineer – Hybrid in Toronto

SQL
Python
Communication Skills
Data Engineering
Problem-Solving Skills
Data Pipeline Development
ETL/ELT Processes