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- Employment type
- Full-time
- Experience level
- Mid-level · 2+ years
- Minimum education
- Bachelor’s degree
- Posting language
- English
- Working hours
- 40 hours per week
- Seniority
- Mid-Senior level
- Application method
- Direct apply is available
Job summary
Build and support data engineering solutions using ETL/ELT processes and cloud data platforms. Work with data warehousing and lakehouse architectures, along with tools for data processing, orchestration, and streaming.
Job details
🔹 1. Data Engineer 📍 Canada – Hybrid Experience: 1–4 Years Key Skills: Python, SQL, PySpark Databricks, Apache Spark, Delta Lake AWS / Azure / GCP Snowflake, BigQuery, Synapse, ADF, Redshift, or AWS Glue Airflow, Kafka, CI/CD, Git ETL/ELT, Data Warehousing & Lakehouse Architecture ✅ Eligibility only Valid PGWP holders or Open work permit Must be authorized to work in Canada Bachelor's degree in Computer Science, Engineering, or related field, or equivalent experience
What you’ll do
Build and support data engineering solutions using ETL/ELT processes and cloud data platforms. Work with data warehousing and lakehouse architectures, along with tools for data processing, orchestration, and streaming.
Requirements
Candidates should have 1–4 years of experience and skills in Python, SQL, PySpark, and relevant data engineering technologies. A bachelor's degree in Computer Science, Engineering, or a related field, or equivalent experience, is required; applicants must be authorized to work in Canada and hold a valid PGWP or open work permit.
Listed skills
- Microsoft Azure · Preferred
- SQL · Preferred
- Amazon Web Services · Preferred
- Python · Preferred
Other relevant skills
Identified from the job description. Confirm important requirements above.
- Python
- SQL
- PySpark
- Databricks
- Apache Spark
- Delta Lake
- AWS
- Azure
- Google Cloud Platform
- Snowflake
- BigQuery
- Azure Synapse
- Azure Data Factory
- Amazon Redshift
- AWS Glue
- Airflow
Job areas
- Data & Analytics
- Technology
- Software
- Engineering
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