ZipRecruiter

Log In

2

Remote Data Engineer Jobs in Toronto, ON (NOW HIRING)

Morson Talent

25-026 DevOps Engineer

Toronto, ON · Remote

CA$80 - CA$100/hr

MP4 Hourly Rate: $80 - 100/hour Duration: 10 Months Hours of work: 35 Location: 700 University Avenue, Toronto (100% Remote) Job Overview We are seeking a skilled DevOps Engineer to support our data ...

SpryPoint

Data Developer

Toronto, ON · Remote

CA$800/wk

As a Data Developer, you'll play an important role in turning data into meaningful insights by ... Remote-first environment, flexible working hours across North America, and hub offices in ...

New

Morson Talent

25-053 Data Architect

Pickering, ON · On-site +1

$85 - $100/hr

... remote) Job Overview JOB FUNCTION As a Data Architect you will be responsible for leading the Azure ... engineers, data analysts and solution architects to develop data pipelines to feed our data ...

Mercor

Network Engineer - Data Annotation

Toronto, ON · Remote

CA$50 - CA$70/hr

Position: Network Engineer - Data for Autonomous Systems annotation Type: Contract Compensation ... Remote Commitment: 30-40 hours/week Role Responsibilities * Review real-world data from deployed ...

Morson Talent

25-125 FinOps Engineer

Pickering, ON · Remote

$80 - $95/hr

MP4, $80- $95/hr INC Duration: 12 Months Hours of work: 35 Location: (Hybrid - 1 day remote) Temp ... Data Engineering: Build and maintain ETL pipelines using Python to collect, transform, and ...

Mercor

Network Engineer - Data Annotation

Toronto, ON · Remote

CA$50 - CA$70/hr

Position: Network Engineer - Data for Autonomous Systems annotation Type: Contract Compensation ... Remote Commitment: 30-40 hours/week Role Responsibilities * Review real-world data from deployed ...

MCKESSON

Senior Data Specialist

Mississauga, ON · Remote

Key Responsibilities Azure Databricks & Data Engineering * Design, build, and optimize large-scale data pipelines using Azure Databricks, PySpark, and advanced SQL. * Develop and maintain batch and ...

McKesson

Senior Data Specialist

Mississauga, ON · Remote

Key Responsibilities Azure Databricks & Data Engineering * Design, build, and optimize large-scale data pipelines using Azure Databricks, PySpark, and advanced SQL. * Develop and maintain batch and ...

McKesson

Senior Data Specialist

Mississauga, ON · Remote

Key Responsibilities Azure Databricks & Data Engineering * Design, build, and optimize large-scale data pipelines using Azure Databricks, PySpark, and advanced SQL. * Develop and maintain batch and ...

Derivative Path

Applied AI Engineer

Toronto, ON · Remote

CA$110K - CA$150K/yr

Own the data engineering layer that feeds AI systems: pipelines, retrieval architectures, context ... Fully remote * RRSP contribution at 3% * Competitive health benefits T he expected salary for ...

previous page

Showing results 41-60

All JobsData Engineer JobsRemote Data Engineer JobsRemote Data Engineer Jobs in Toronto, ON

Remote Data Engineer information

See Toronto, ON salary details

$65.4K

$121.5K

$154.6K

How much do remote data engineer jobs pay per year?

As of Aug 24, 2026, the average yearly pay for remote data engineer in Toronto, ON is $121,504.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,886.00 and $138,379.00 per year, depending on experience, location, and employer.

What is a remote data engineer?

A Remote Data Engineer is a professional who designs, builds, and maintains data pipelines, databases, and data processing systems while working from a location outside of a traditional office. They collaborate with data scientists, analysts, and other stakeholders to ensure data is collected, stored, and made accessible efficiently and securely. Remote Data Engineers use programming languages like Python or Scala, work with technologies such as SQL, Hadoop, or cloud platforms, and address challenges related to data quality and scalability. Their remote role allows them to work for companies regardless of geographic location, often relying on virtual collaboration tools to stay connected with their teams.

What does a remote data engineer do?

As a remote data engineer, you focus on collecting, storing, and organizing large amounts of information. You work from home to design, develop, and maintain systems for the mining, warehousing, and processing of data. A data engineer communicates with employers, clients, or other data professionals to assess the needs of the project and develop and implement solutions to meet those needs. Data engineers also take steps to manage current database architecture and make updates when needed. Remote engineers typically handle their responsibilities in a cloud-based environment using “big data” tools, such as Amazon Web Services (AWS) and SQL.

What are the key skills and qualifications needed to thrive as a remote data engineer, and why are they important?

To thrive as a Remote Data Engineer, you need strong programming skills in languages like Python or Scala, expertise in SQL, data modeling, and a background in computer science or a related field. Familiarity with cloud platforms (such as AWS, Azure, or GCP), big data tools (like Hadoop and Spark), and certifications in cloud or data engineering are highly valued. Excellent problem-solving, communication, and self-management skills help remote data engineers collaborate effectively and stay productive in a distributed environment. These competencies ensure reliable data pipelines, scalable solutions, and seamless teamwork, which are critical for organizational success in data-driven projects.

How do remote data engineers typically collaborate with other team members across different time zones?

Remote Data Engineers often work with cross-functional teams, including data scientists, analysts, and software engineers, many of whom may be located in different parts of the world. Collaboration is usually facilitated through project management tools, version control platforms, and regular virtual meetings. It’s common to have a mix of synchronous check-ins and asynchronous communication, allowing for flexible scheduling and efficient handoffs. Strong written communication skills and proactive status updates are essential for staying aligned with team objectives and project deadlines.

What is the difference between Remote Data Engineer vs Remote Data Analyst?

AspectRemote Data EngineerRemote Data Analyst
Required CredentialsBachelor's in CS, Data Science, or related; SQL, Python, cloud certificationsBachelor's in Statistics, Data Science, or related; SQL, Excel, visualization tools
Work EnvironmentCollaborates with data engineering teams, cloud platforms, big data toolsWorks with business teams, dashboards, reporting tools
Industry UsageTech, finance, healthcare, e-commerceMarketing, finance, retail, healthcare
Common Search IntentBuilding data pipelines, data infrastructureData reporting, insights, visualization

Remote Data Engineers focus on designing and maintaining data pipelines and infrastructure, often requiring programming and cloud skills. Remote Data Analysts interpret data, create reports, and provide insights using visualization tools. While both roles work with data, their responsibilities and skill sets differ, making each suited for different career paths within data teams.

Are remote data engineers still in demand?

Remote data engineers are currently in high demand due to the increasing reliance on data-driven decision making and cloud-based data platforms. Skills in SQL, Python, cloud services, and data pipeline tools are highly sought after, and many organizations continue to hire for remote roles to access a broader talent pool.

Can a remote data engineer work remotely?

Yes, remote data engineers can work remotely, as the role primarily involves managing data pipelines, databases, and cloud-based tools that can be accessed from anywhere with an internet connection. Many companies offer remote positions for data engineers, often requiring skills in SQL, Python, cloud platforms, and data architecture. However, some roles may require occasional on-site presence or specific certifications depending on the employer's policies.
More about Remote Data Engineer jobs

What are the most commonly searched types of Data Engineer jobs in Toronto, ON?

The most popular types of Data Engineer jobs in Toronto, ON are:

What are popular job titles related to Remote Data Engineer jobs in Toronto, ON?

For Remote Data Engineer jobs in Toronto, ON, the most frequently searched job titles are:

What job categories do people searching Remote Data Engineer jobs in Toronto, ON look for?

The top searched job categories for Remote Data Engineer jobs in Toronto, ON are:

What cities near Toronto, ON are hiring for Remote Data Engineer jobs?

Cities near Toronto, ON with the most Remote Data Engineer job openings:

Remote Data Engineer jobs near you
Infographic showing various Remote Data Engineer job openings in Toronto, ON as of August 2026, with employment types broken down into 50% Full Time, and 50% Contract. Highlights an 100% Remote job distribution, with an average salary of $121,504 per year, or $58.4 per hour.

25-026 DevOps Engineer

Morson Talent

Toronto, ON • Remote

CA$80 - CA$100/hr

Full-time

Re-posted 17 days ago

Job description

Job Description Number of Vacancies: 1 Level: MP4 Hourly Rate: $80 - 100/hour Duration: 10 Months Hours of work: 35 Location: 700 University Avenue, Toronto (100% Remote) Job Overview We are seeking a skilled DevOps Engineer to support our data analytics developers in deploying, maintaining, and troubleshooting data pipelines within our Azure-based Data Lake environment. This role will be responsible for managing Cl/CD pipelines, ensuring seamless code deployment from development to UAT and production, and establishing best practices for DevOps in our data engineering and analytics functions, specifically, we are standing up a Centre of Advanced Analytics and need dedicated expertise and support. The ideal candidate will bring expertise in cloud-based DevOps, data pipeline automation, and infrastructure management, enabling our team to focus on delivering high-quality data products efficiently.

Key Responsibilities: Deployment & Environment Management Design, implement, and maintain Cl/CD pipelines for deploying data pipelines and analytics models into UAT and Production environments. Support the data development team by automating code deployments, reducing manual errors, and improving deployment efficiency. Troubleshoot and resolve pipeline failures, deployment issues, and infrastructure bottlenecks in collaboration with data developers.

Manage and optimize data lake infrastructure, security, and access controls to ensure smooth operations. DevOps Best Practices & Standardization Establish and enforce DevOps standards, best practices, and documentation to improve efficiency and reliability in data product development. Develop automated testing strategies for data pipelines to validate transformations, integrity, and performance across environments.

Work with cross-functional teams to implement observability and monitoring solutions for data workflows and deployments. Enhance version control practices and facilitate collaboration using Git, Azure DevOps, or similar tools. Infrastructure & Performance Optimization Maintain and optimize cloud-based data lake environments (Azure, Databricks, Synapse) for efficient data processing and analytics.

Automate infrastructure provisioning and configuration using Infrastructure as Code (laC) (Terraform, ARM Templates, etc.). Identify and resolve performance bottlenecks in data processing pipelines. Assist in defining and implementing security, access management, and governance policies for data and analytics environments

Collaboration & Stakeholder Engagement Act as a liaison between the Data Analytics team and the Data Lake Engineering team to ensure smooth deployments. Work closely with Data Developers, Data Engineers, and Analytics teams to troubleshoot and optimize workflows. Provide guidance and mentorship to team members on DevOps principles, automation, and best practices.

Qualifications 3+ years of experience in DevOps, Cloud Engineering, or Data Engineering with a strong focus on Cl/CD and automation. Additional MLOps experience a nice to have. Strong expertise in Cl/CD tools such as Azure DevOps, GitHub Actions, Jenkins, or GitLab Cl/CD.

Experience working with Azure-based data platforms such as Azure Data Lake, Azure Synapse, Azure Databricks. Proficiency in scripting and automation Understanding of monitoring, logging, and alerting solutions for data pipelines (Azure Monitor). Knowledge of security, access management, and compliance standards for data environments.

Strong problem-solving skills and the ability to debug complex deployment and pipeline issues. Ability to work collaboratively Experience with Databricks workflow automation, Delta Lake, Azure

Apply