ZipRecruiter

Log In

1

Python Data Analysis Jobs in Montreal, QC (NOW HIRING)

Artefact

Sr Data Analyst

Montreal, QC · On-site

... of data analysis and business strategies. We are seeking a candidate who not only possesses ... Python, R, SQL * Tool * * Cloud databases * Amazon Redshift, Microsoft Azure, Google BigQuery ...

Broadsign Careers

Data Analyst

Montreal, QC · Hybrid

Innovation & Independent Analysis: You will take ownership of independent coding and analysis ... You should be comfortable coding in Python and have experience with Snowflake and AWS platforms.

Jay Analytix

Python Developer + Pricing

Montreal, QC · On-site

Role Overview We are seeking a Python Developer with experience in pricing models and banking ... data (interest rates, volatility, curves) * Optimize performance of pricing engines and analytics ...

Averna

Data Analyst (English version)

Montreal, QC · Remote

Data Analyst Role Summary As a Data Analyst, you will support business decision-making by gathering ... analysis, and coding (e.g. SQL, Python, R). * Proven experience creating dashboards, reports, and ...

Levio

Python Developer

Montreal, QC · Hybrid

Levio is currently seeking a Python Developer to contribute to a largescale project based in ... data and infrastructure teams to ensure smooth integration of solutions ; * Analyze technical ...

next page

Showing results 1-20

All JobsPython Data Analysis JobsPython Data Analysis Jobs in Montreal, QC

Python Data Analysis information

See Montreal, QC salary details

$22.9K

$103.9K

$187.5K

How much do python data analysis jobs pay per year?

As of Aug 20, 2026, the average yearly pay for python data analysis in Montreal, QC is $103,933.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,332.00 and $139,107.00 per year, depending on experience, location, and employer.

What is a python data analysis?

A Python Data Analysis job involves using Python programming to collect, clean, analyze, and visualize data for insights and decision-making. Professionals in this role use libraries like Pandas, NumPy, and Matplotlib to manipulate datasets and perform statistical analysis. They may work in various industries, solving business problems, identifying trends, and supporting data-driven strategies. Strong programming skills, data wrangling expertise, and knowledge of analytical techniques are essential for success in this field.

What are the typical responsibilities of someone working in python data analysis?

Professionals in Python Data Analysis are usually responsible for collecting, cleaning, and analyzing datasets to uncover trends and inform business strategies. Their daily tasks often include writing Python scripts, visualizing data, conducting statistical analyses, and preparing reports that summarize their findings for both technical and non-technical audiences. Collaboration with data engineers, business analysts, and project managers is common, ensuring that data solutions align with organizational goals. This role offers opportunities to build expertise in specialized areas, such as machine learning or business intelligence, and can lead to career advancement in data science or analytics leadership positions.

What are the key skills and qualifications needed to thrive in python data analysis, and why are they important?

To thrive in a Python Data Analysis role, you need strong proficiency in Python programming, statistical analysis, and data wrangling, often backed by a degree in computer science, mathematics, or a related field. Familiarity with tools such as Pandas, NumPy, Jupyter Notebook, and visualization libraries like Matplotlib or Seaborn, along with potential certifications in data analysis or Python, is highly valuable. Analytical thinking, attention to detail, and effective communication help translate complex data findings into actionable insights for stakeholders. These capabilities are crucial for transforming raw data into meaningful information that supports business decision-making.

What are the most commonly searched types of Python Data Analysis jobs in Montreal, QC?

The most popular types of Python Data Analysis jobs in Montreal, QC are:

What are popular job titles related to Python Data Analysis jobs in Montreal, QC?

For Python Data Analysis jobs in Montreal, QC, the most frequently searched job titles are:

What job categories do people searching Python Data Analysis jobs in Montreal, QC look for?

The top searched job categories for Python Data Analysis jobs in Montreal, QC are:

Python Data Analysis jobs near you
Infographic showing various Python Data Analysis job openings in Montreal, QC as of August 2026, with employment types broken down into 1% As Needed, 83% Full Time, 10% Part Time, 5% Contract, and 1% Nights. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $103,933 per year, or $50 per hour.

Data Integration Engineer

GFR Technologies SE

Montreal, QC • Remote

Full-time

Posted 14 days ago

Job description

Data Integration Engineer (Azure & Databricks)

Location: Canada (Hybrid/Remote)
Experience: 5-8 Years

Position Overview

We are seeking a hands-on Data Integration Engineer to join our growing data and analytics team. This role is focused on the design, development, enhancement, and support of enterprise data integration solutions within an Azure and Databricks ecosystem.

The ideal candidate is an execution-oriented professional who enjoys building and supporting data pipelines, integrating data from multiple source systems, and implementing scalable modern data platform solutions. While the role requires participation in solution discussions, the primary focus is on delivery, implementation, and operational support, rather than enterprise architecture or strategic consulting.

Key Responsibilities

Data Integration & Engineering

  • Design, develop, and maintain scalable data integration pipelines using Azure and Databricks.
  • Build and support batch and near real-time data ingestion processes from multiple internal and external source systems.
  • Develop data transformation logic to support analytics, reporting, and business consumption requirements.
  • Implement data quality, validation, reconciliation, and monitoring processes.
  • Optimize pipeline performance and troubleshoot production issues.

Databricks Development

  • Develop and maintain Databricks notebooks, workflows, and processing pipelines.
  • Build transformation frameworks using Spark and Databricks best practices.
  • Support data ingestion, cleansing, enrichment, and aggregation activities.
  • Work with large and complex datasets across multiple domains.

Azure Data Platform Delivery

  • Develop solutions using Azure data services including:
    • Azure Data Factory (ADF)
    • Azure Data Lake Storage (ADLS)
    • Azure Databricks
    • Azure SQL
    • Azure Synapse (preferred)
  • Support deployment, monitoring, and operational activities across the data platform.

Data Architecture Implementation

  • Implement and support Medallion Architecture (Bronze, Silver, Gold layers).
  • Ensure data lineage, governance, and consistency across the platform.
  • Contribute to data modeling and solution design discussions.
  • Translate architectural direction into technical implementation and delivery.

Team Collaboration

  • Collaborate closely with Data Engineers, Solution Architects, Product Owners, and Business Stakeholders.
  • Support ongoing initiatives and enhancements within an established delivery team.
  • Participate in Agile ceremonies, sprint planning, estimation, and backlog refinement.
  • Assist in production support, troubleshooting, and continuous improvement initiatives.

Required Qualifications

  • 5-8 years of experience in Data Engineering, Data Integration, or Data Platform Development.
  • Strong hands-on experience with Azure Databricks.
  • Proven experience building and supporting enterprise-scale data pipelines.
  • Strong understanding of data ingestion, transformation, and integration patterns.
  • Experience integrating data from multiple source systems and platforms.
  • Solid understanding of modern data lake and lakehouse architectures.
  • Experience implementing Medallion Architecture concepts.
  • Strong SQL development and data analysis skills.
  • Experience working within Agile delivery teams.

Technical Skills

Required

  • Azure Databricks
  • Apache Spark / PySpark
  • Azure Data Factory (ADF)
  • Azure Data Lake Storage (ADLS)
  • SQL
  • Python
  • Data Integration & ETL/ELT Development
  • Data Quality & Reconciliation

Preferred

  • Azure Synapse Analytics
  • Delta Lake
  • CI/CD for Data Pipelines
  • Azure DevOps
  • Git
  • Kafka or Event-Driven Architectures
  • Power BI

Preferred Experience

  • Experience supporting cloud-based analytics and reporting platforms.
  • Experience working with complex enterprise data ecosystems.
  • Exposure to financial services, insurance, banking, or regulated industries.
  • Experience supporting production environments and ongoing operational initiatives.
  • Familiarity with data governance and data management best practices.

Apply