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Synechron

Python Developer – Data Engineer

Toronto, ON, Canada

Pay: $100,000 to $125,000 CAD / year
Job type: Full-time
Apply by: Oct 29, 2026
Posting language: English
Posted: Sep 29, 2026

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Original job description

We are

At Synechron, we believe in the power of digital to transform businesses for the better. Our global consulting firm combines creativity and innovative technology to deliver industry-leading digital solutions. Synechron’s progressive technologies and optimization strategies span end-to-end Artificial Intelligence, Consulting, Digital, Cloud & DevOps, Data, and Software Engineering, servicing an array of noteworthy financial services and technology firms. Through research and development initiatives in our FinLabs we develop solutions for modernization, from Artificial Intelligence and Blockchain to Data Science models, Digital Underwriting, mobile-first applications and more. Over the last 20+ years, our company has been honored with multiple employer awards, recognizing our commitment to our talented teams. With top clients to boast about, Synechron has a global workforce of 17,000+, and has 58 offices in 22 countries within key global markets.

Our challenge

We are seeking a skilled Python Developer – Data Engineering to join our data engineering team. In this role, you will design, develop, and maintain high-performance data processing pipelines using modern Python frameworks and tools.

You will work with large-scale datasets, containerized applications, distributed computing platforms, messaging systems, and analytical databases to deliver scalable, reliable, and efficient data solutions.

Additional Information*

The base salary for this position will vary based on geography and other factors. In accordance with law, the base salary for this role if filled within Toronto, ON is CAD $100K - CAD $125K/year & benefits (see below).

The Role

Responsibilities:

Develop and optimize data manipulation and transformation workflows using pandas and Polars.
Design, build, and maintain efficient data processing pipelines for large-scale datasets.
Optimize Python code and data workflows for performance, scalability, and memory efficiency.
Develop containerized applications using Docker and deploy scalable services using Kubernetes.
Build and maintain data pipelines integrated with ClickHouse or similar columnar databases for analytical workloads.
Design and implement event-driven architectures using NATS for asynchronous data processing and messaging.
Develop distributed computing solutions using Dask to process datasets that exceed single-machine memory limitations.
Write and maintain comprehensive unit and integration tests using pytest.
Maintain high code quality, test coverage, reliability, and performance standards.
Use Git for version control and follow established branching, code review, and collaboration practices.
Collaborate with data engineers, software developers, DevOps teams, and other stakeholders to deliver reliable data solutions.
Troubleshoot production issues and support the continuous improvement of data engineering processes.

Requirements:

Bachelor’s degree in computer science or Diploma in IT with equivalent experience.

Python and Data Processing

Advanced proficiency in Python.
Strong experience with pandas and Polars for data manipulation, transformation, and analysis.
Experience working with large datasets and optimizing code for performance and memory usage.
Strong understanding of Python development best practices, object-oriented programming, and clean code principles.

Containerization and Orchestration

Hands-on experience building and managing container images using Docker.
Experience creating and maintaining multi-container applications.
Working knowledge of Kubernetes for container orchestration, deployment, scaling, and service management.

Data Infrastructure

Experience with ClickHouse or a similar columnar database.
Understanding of OLAP workloads, analytical queries, data modeling, and query optimization.
Experience designing data pipelines for analytical and reporting use cases.

Messaging and Streaming

Familiarity with NATS.io and message-driven architectures.
Understanding of asynchronous processing, event-driven systems, messaging patterns, and distributed workflows.

Testing and Quality Assurance

Proficiency with pytest.
Experience writing unit tests, integration tests, and regression tests.
Understanding of test coverage, mocking, test automation, and quality assurance practices.

Distributed Computing

Experience with Dask for parallel processing and out-of-core computation.
Understanding of distributed data processing and techniques for handling datasets that exceed available system memory.

Version Control

Strong command of Git, including branching strategies, pull requests, code reviews, merging, and conflict resolution.
Experience collaborating through shared code repositories and following software development best practices.

Preferred skills:

Experience with additional Python libraries for data science, analytics, or machine learning.
Familiarity with CI/CD pipelines and DevOps practices.
Experience with cloud platforms and cloud-based data engineering solutions.
Knowledge of data orchestration tools and workflow scheduling platforms.
Experience working with financial services, capital markets, trading, or other high-volume data systems.
Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related field.

We offer:

A multinational organization with 58 offices in 22 countries and the possibility to work abroad.
15 days (3 weeks) of paid annual leave plus an additional 10 days of personal leave (floating days and sick days).
A comprehensive insurance plan including medical, dental, vision, life insurance, and long-term disability.
Flexible hybrid policy.
RRSP with employer’s contribution up to 4%.
A higher education certification policy.
On-demand Udemy for Business for all Synechron employees with free access to more than 5000 curated courses.
Coaching opportunities with experienced colleagues from our Financial Innovation Labs (FinLabs) and Center of Excellences (CoE) groups.
Cutting edge projects at the world’s leading tier-one banks, financial institutions and insurance firms.
A truly diverse, fun-loving and global work culture.

S YNECHRON’S DIVERSITY & INCLUSION STATEMENT

Diversity & Inclusion are fundamental to our culture, and Synechron is proud to be an equal opportunity workplace and is an affirmative action employer. Our Diversity, Equity, and Inclusion (DEI) initiative ‘Same Difference’ is committed to fostering an inclusive culture – promoting equality, diversity and an environment that is respectful to all. We strongly believe that a diverse workforce helps build stronger, successful businesses as a global company. We encourage applicants from across diverse backgrounds, race, ethnicities, religion, age, marital status, gender, sexual orientations, or disabilities to apply. We empower our global workforce by offering flexible workplace arrangements, mentoring, internal mobility, learning and development programs, and more.

All employment decisions at Synechron are based on business needs, job requirements and individual qualifications, without regard to the applicant’s gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law.

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More about this job

Requirements

Requires advanced Python proficiency, strong experience with pandas and Polars, and practical knowledge of Docker, Kubernetes, ClickHouse or a similar columnar database, NATS, Dask, pytest, and Git. A bachelor’s degree in computer science or an IT diploma with equivalent experience is required, along with experience optimizing large-scale data processing for performance and memory efficiency.

Skills

Python
Pandas
Polars
Docker
Kubernetes
ClickHouse
NATS
Dask
Pytest
Git
Data Pipeline Development
Distributed Computing
Data Modeling
OLAP
Performance Optimization
Event-Driven Architecture

Benefits

Paid Annual Leave
Personal Leave
Medical Insurance
Dental Insurance
Vision Insurance
Life Insurance
Long-Term Disability Insurance
Hybrid Work Policy
RRSP With Employer Contributions Up To 4%
Higher Education Certification Policy
Udemy For Business Access
Coaching And Mentoring Opportunities
International Work Opportunities
Learning And Development Programs

Visa sponsorship

Not detected in the job text

Keywords

Python
Pandas
Polars
Docker
Kubernetes
ClickHouse
NATS
Dask
Pytest
Git
Data Engineering
Data Processing Pipelines
Large-Scale Datasets
Distributed Computing
Out-Of-Core Computation
Columnar Databases
OLAP
Analytical Queries
Data Modeling
Query Optimization
Event-Driven Architecture
Asynchronous Processing
Message-Driven Architecture
Unit Testing
Integration Testing
Regression Testing
CI/CD
DevOps
Cloud Platforms
Financial Services

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