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Data Engineer
- Toronto, ON, Canada
Full-time
This opening has closed.
The original listing is kept below for reference.
Job details
- Job type
- Full-time
- Closing date
- Posting language
- English
- Posted
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Archived listing. The details below describe a past opening.
Role Description This is a full-time, on-site Data Engineer role based in Toronto, ON. The Data Engineer will design, build, and maintain scalable data pipelines and infrastructure to support analytics and reporting needs. Daily responsibilities include implementing and optimizing ETL processes, developing data models, and integrating data from various internal and external sources. The role involves collaborating closely with data analysts, data scientists, and software engineers to ensure data is clean, reliable, and accessible. The Data Engineer will also monitor data systems for performance and reliability, troubleshoot issues, and contribute to documentation and best practices.
Qualifications
- Strong data engineering skills, including experience building and maintaining data pipelines and working with large datasets.
- Proficiency in data modeling and data warehousing, with the ability to design efficient schemas and storage structures.
- Hands-on experience with Extract Transform Load (ETL) processes and tools, including data integration and transformation workflows.
- Ability to perform data analytics, including querying, profiling, and interpreting data to support business and technical stakeholders.
- Experience with SQL and at least one programming language commonly used in data engineering (such as Python or Scala).
- Familiarity with cloud data platforms and services (e.g., AWS, Azure, or GCP) and modern data stack tools is beneficial.
- Understanding of data governance, data security, and best practices for data quality and reliability.
- Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field, or equivalent practical experience.
- Ability to work collaboratively in an on-site environment, communicate clearly, and manage multiple priorities effectively.
More about this job
Responsibilities
Design, build, and maintain scalable data pipelines and infrastructure, including ETL processes, data models, and integrations from internal and external sources. Monitor and troubleshoot data systems, ensure data is reliable and accessible, and collaborate with analysts, scientists, and engineers on analytics and reporting needs.
Requirements
Requires data engineering experience with pipelines, large datasets, data modeling, warehousing, ETL, analytics, and SQL plus a programming language such as Python or Scala. A bachelor’s degree in a related field or equivalent practical experience is required, along with knowledge of cloud platforms, governance, security, and data quality practices.
Skills
- Data Engineering
- Data Pipelines
- ETL
- Data Modeling
- Data Warehousing
- SQL
- Python
- Scala
- Data Analytics
- Data Integration
- Cloud Data Platforms
- Data Governance
- Data Security
- Data Quality
- Troubleshooting
- Collaboration
Visa sponsorship
Not detected in the job text
Categories
- Data & Analytics
- Technology
- Software
- Engineering
Keywords
- Data Engineering
- Data Pipelines
- ETL
- Data Modeling
- Data Warehousing
- SQL
- Python
- Scala
- AWS
- Azure
- GCP
- Cloud Data Platforms
- Data Integration
- Data Transformation
- Data Analytics
- Large Datasets
- Data Governance
- Data Security
- Data Quality
- Data Reliability
- Data Infrastructure
- Analytics
- Reporting
- Data Profiling
- Performance Monitoring
- Troubleshooting
- Modern Data Stack
- Data Schemas
- Documentation