Data Engineer

Insight Global; Montreal; Hybrid; CAD 68,880 - 82,656; Full time

Job summary

A strategic staffing and consulting agency is seeking a Data Engineer to design and implement data pipelines for a banking client. The ideal candidate has over 4 years of experience with Python, Databricks, and Snowflake. This position is full-time and hybrid, requiring candidates to be local to the Montreal area. Responsibilities include building ETL pipelines, collaborating in an Agile environment, and maintaining data workflows for accuracy and performance.

Qualifications

• 4+ years of experience in data engineering and related technologies.
• Strong Python experience (Pandas, NumPy, PySpark).
• Familiarity with ETL principles and data modeling.

Responsibilities

• Build and optimize ETL pipelines for data transformation.
• Collaborate with cross-functional teams in an Agile environment.
• Develop and maintain data workflows, ensuring accuracy and performance.

Job description

Base pay range

$50.00/hr - $60.00/hr

📍 Location: Montreal, QC (Hybrid – 3 days onsite) - candidates MUST be local to Montreal area to be considered.

📅 Contract: 12 months (with possible extensions)

💰 Rate: Up to $60/hr

About the Role:

We’re seeking a Data Engineer with 4+ years of experience to join our team and support a strategic banking client. This role involves designing and implementing scalable data pipelines and ETL processes using Python, Databricks, and Snowflake.

Key Responsibilities:

• Build and optimize ETL pipelines for data transformation
• Collaborate with cross-functional teams in an Agile environment
• Develop and maintain data workflows, ensuring accuracy and performance
• Implement testing and CI/CD for reliable deployments
• Work with cloud platforms and big data technologies

Must-Have Skills:

• Strong Python experience (Pandas, NumPy, PySpark)
• Expertise in Databricks and Snowflake
• Solid understanding of ETL principles and data modeling
• Familiarity with Agile methodologies
• Experience with big data tools (Spark, Hadoop)

Nice-to-Have:

• Knowledge of regulatory requirements

Seniority level

• Associate

Employment type

• Full-time

Job function

• Engineering and Information Technology

Industries

• Information Services, Data Infrastructure and Analytics, and IT System Data Services