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Python Analytics Jobs in Ontario (NOW HIRING)

Releady

Senior Backend Engineer (SQL/Python)

Toronto, ON · On-site +1

CA$135/hr

The ideal candidate has hands-on experience with FastAPI (or similar Python frameworks), strong SQL proficiency, and experience working with analytics, reporting, or data-heavy applications in ...

Faire

Senior Platform Analytics Engineer

Kitchener, ON · On-site

CA$160K - CA$220K/yr

Strong SQL and Python skills and demonstrated competencies in designing well-architected data ... Analytics engineering experience with a focus on data modeling, large-scale data processing, and ...

Dialpad

Analytics Engineer

Kitchener, ON · On-site

Proficiency in Python for data exploration and analysis. * Hands-on experience with Agile Software Development methodologies and tools like Jira. * Working experience in cloud-based data platforms ...

Scotiabank

Manager, Analytics

Toronto, ON · On-site

The Business Analytics Channels & Servicing Team partners with stakeholders in channel management ... Programming Language: at least one of SQL, Python, R, SAS * Experience in Banking/Financial ...

Robinhood

Analytics Developer

Toronto, ON · On-site

Robinhood's Analytics Engineering team, part of the Data Science organization, builds the data ... You have strong experience with SQL, Python, and Apache Spark for data processing * You have ...

Viral Nation Inc.

Analytics Lead

Toronto, ON

CA$110K - CA$140K/yr

Deep technical proficiency in analytics and BI technologies, including Python and SQL for analysis and data modeling, Google Cloud Platform, BigQuery, and Snowflake for data infrastructure, and BI ...

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All JobsPython Analytics JobsPython Analytics Jobs in Ontario

Python Analytics information

What is the salary of a Python analyst?

The salary of a Python analyst typically ranges from $60,000 to $110,000 annually, depending on experience, location, and industry. Professionals with strong skills in data analysis, machine learning, and proficiency in tools like Pandas and Jupyter Notebook tend to earn higher salaries.

What are the key skills and qualifications needed to thrive as a Python Analytics professional, and why are they important?

To thrive as a Python Analytics professional, you need a strong background in statistics, data analysis, and proficiency in Python programming, often supported by a degree in computer science, mathematics, or a related field. Familiarity with data analytics libraries (such as pandas, NumPy, and scikit-learn), data visualization tools, and experience with databases are typically required. Strong problem-solving, communication, and critical thinking skills help in interpreting data and conveying insights to stakeholders. These abilities are crucial for turning complex data into actionable business decisions and driving organizational success.

Is Python good for data analysts?

Python is widely used by data analysts due to its simplicity, extensive libraries like pandas and NumPy, and strong community support. It enables efficient data manipulation, analysis, and visualization, making it a valuable skill for the role.

Can I be a data analyst in 3 months?

Becoming a data analyst with a focus on Python typically requires several months of dedicated learning, including skills in data manipulation, visualization, and tools like pandas and SQL. While some individuals may acquire foundational skills in three months, gaining proficiency for a professional role usually takes longer and depends on prior experience and learning pace.

What is the difference between Python Analytics vs Data Analyst?

AspectPython AnalyticsData Analyst
Required SkillsPython programming, data manipulation, statistical analysisExcel, SQL, basic statistics
CertificationsPython certifications, data analysis coursesNone typically required, but certifications like CAP or Microsoft certifications are common
Work EnvironmentData science teams, analytics departments, tech companiesBusiness units, marketing, finance, consulting firms
ToolsPython libraries (Pandas, NumPy, scikit-learn)Excel, SQL, Tableau, Power BI

Python Analytics involves using Python programming to perform advanced data analysis, modeling, and automation, often requiring coding skills. Data Analysts focus on interpreting data using tools like Excel and SQL, providing reports and insights. While both roles analyze data, Python Analytics typically involves more technical and programming expertise, making it suitable for complex data projects and predictive modeling.

Is Python still in demand?

Python analytics roles remain highly in demand due to Python's versatility in data analysis, machine learning, and automation. Employers seek professionals skilled in libraries like Pandas, NumPy, and frameworks such as TensorFlow, often requiring proficiency in data visualization and scripting. Staying updated with Python versions and related tools enhances job prospects in this field.

What are some typical challenges faced by professionals in Python Analytics roles, and how can I prepare for them?

Professionals in Python Analytics roles often encounter challenges such as handling large and complex datasets, ensuring data quality, and communicating insights effectively to non-technical stakeholders. To prepare, it's beneficial to strengthen your skills in data cleaning, visualization libraries (like Matplotlib or Seaborn), and learn best practices for writing efficient, reproducible code. Collaborating closely with data engineers, business analysts, and decision-makers is also a key part of the job, so developing strong communication and teamwork abilities will help you succeed.

What is a Python Analytics professional?

A Python Analytics professional is someone who uses the Python programming language to collect, process, analyze, and interpret data in order to help organizations make data-driven decisions. They often work with large datasets, perform statistical analyses, create data visualizations, and build predictive models. These professionals may work in industries such as finance, healthcare, marketing, or technology, and typically use libraries like Pandas, NumPy, and Matplotlib. Their work helps businesses gain insights, optimize processes, and solve complex problems through data.
What are popular job titles related to Python Analytics jobs in Ontario? For Python Analytics jobs in Ontario, the most frequently searched job titles are:
What job categories do people searching Python Analytics jobs in Ontario look for? The top searched job categories for Python Analytics jobs in Ontario are:
Python Analytics jobs near you
Infographic showing various Python Analytics job openings in Ontario as of June 2026, with employment types broken down into 81% Full Time, 13% Part Time, 4% Temporary, and 2% Contract. Highlights an 80% Physical, 6% Hybrid, and 14% Remote job distribution.

Senior Backend Engineer (SQL/Python)

Releady

Toronto, ON • On-site, Remote

CA$135/hr

Contractor

Posted 2 days ago

Job description

OVERVIEW

We are seeking a Senior Backend Engineer with strong expertise in Python and API development to design and build scalable, data-driven backend systems. This role focuses on developing secure RESTful APIs, building ETL frameworks, and integrating data across cloud-native environments.

The ideal candidate has hands-on experience with FastAPI (or similar Python frameworks), strong SQL proficiency, and experience working with analytics, reporting, or data-heavy applications in enterprise environments.

Contract: 9-12 months, potential to extend / convert
Fully remote but must be able to come into the office in financial district (Toronto) for meetings at times
8am - 5pm
Hourly Rate: $135 (incorporated); $117 (T4)
RESPONSIBILITIES

  • Design, develop, and maintain scalable RESTful APIs using Python (FastAPI preferred).

  • Build and support ETL/data ingestion frameworks to process structured and semi-structured data.

  • Integrate with internal and external APIs, data platforms, and cloud storage solutions.

  • Write efficient, optimized SQL queries for analytics and reporting use cases.

  • Implement secure authentication and authorization mechanisms (e.g., OAuth2, JWT).

  • Deploy and maintain services in containerized cloud environments (Docker/Kubernetes).

  • Collaborate with cross-functional teams including data engineers, frontend developers, and product stakeholders.

  • Contribute to CI/CD pipelines, testing strategies, and code quality standards.

  • Optimize backend performance, reliability, and scalability for high-volume data systems.

QUALIFICATIONS

  • 5+ years of backend development experience.

  • Strong proficiency in Python and modern API frameworks (FastAPI, Flask, or similar).

  • Solid experience with SQL and relational databases (PostgreSQL, SQL Server, Snowflake, etc.).

  • Experience building ETL pipelines or data processing workflows.

  • Hands-on experience with cloud platforms (AWS, Azure, or GCP).

  • Experience with containerization and orchestration (Docker, Kubernetes).

  • Understanding of secure API development practices (OAuth2, JWT, RBAC).

  • Familiarity with CI/CD pipelines and version control systems (Git).

  • Experience working in enterprise or regulated environments is a plus.

  • Strong problem-solving skills and ability to work independently in a fast-paced environment.

We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, disability status, or other non-merit factor. We are committed to creating a diverse and inclusive environment for all employees.