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

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

Remote within Canada Build the Future of Global Payments Veem is transforming how businesses move ... You will partner closely with executive leadership and teams across Engineering, Product, Data ...

Working across the engineering organisation, you'll act as a senior technical leader: defining and ... Location_ // This role is available on a remote basis for candidates located anywhere on the East ...

Showing results 41-60

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 15, 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 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 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.

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 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 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.

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:

Infographic showing various Remote Data Engineer job openings in Toronto, ON as of June 2026, with employment types broken down into 94% Full Time, 2% Part Time, and 4% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $121,504 per year, or $58.4 per hour.

25-053 Data Architect

Morson Talent

Pickering, ON • On-site, Remote

$85 - $100/hr

Full-time

Re-posted 13 days ago


Job description

Job Description 25-053 Data Architect Resume Due Date: Monday, April 14, 2025 (5:00PM EST) Number of Vacancies: 1 Level: MP6 Hourly Rate: $85 - $100/hour Duration: 12 Months Hours of work: 35 Location: 889 Brock Road, Pickering (Hybrid - 4 days remote) Job Overview JOB FUNCTION As a Data Architect you will be responsible for leading the Azure architecture. design and delivery of data models and data products which enable innovative, customer-centric digital experiences. You will be working as part of a cross-discipline agile team who helps each other solve problems across all business areas.

You will be a thought leader and subject matter expert on data lake & data warehousing and modeling activities for the team and use your influence to ensure that the team produces best-in class data solutions that leverage repeatable, maintainable, and well-documented design patterns. You will employ best practice in development, security, accessibility and design to achieve the highest quality of service for our customers. JOB DUTIES Lead the architecture.

design and oversee implementation of modular and scalable data ELT/ETL pipelines and data infrastructure on Azure and Databricks leveraging the wide range of data sources across the organization Design curated common data models that offer an integrated, business-centric single source of truth for business intelligence, reporting, and downstream system use Work closely with infrastructure and cyber teams to ensure data is secure in transit and at rest Create, guide and enforce code templates for delivery of data pipelines and transformations for structured, semi-structured and unstructured data sets Develop modeling guidelines that ensure model extensibility and reuse by employing industry standard disciplines for building facts, dimensions, bridge, aggregates, slowly changing dimensions and other dimensional and fact optimizations Establish standards database system fields, including primary and natural key combinations that optimize join performance in a multi-domain. multiple subject area physical (structured zone) and semantic model (curated zone) Ensure model extensibility by employing industry standard disciplines for building facts, dimensions, bridge, aggregates, slowly changing dimensions and other dimensional and fact optimizations Transform data and map to more valuable and understandable semantic layer sets for consumption, transitioning from system centric language to business-centric language Collaborate with business analysts, data scientists, data engineers, data analysts and solution architects to develop data pipelines to feed our data marketplace Introduce new technologies to the environment through research and POCs. and prepare POC code designs that can be implemented and productionized by developers Work with tools in the Microsoft Stack; Azure Data Factory, Azure Data Lake, Azure SQL Databases, Azure Data Warehouse, Azure Synapse Analytics Services, Azure Databricks, Microsoft Purview, and Power Bl Work within the agile SCRUM work management framework in delivery of products and services, including contributing to feature & user story backlog item development, and utilizing related Kanban/SCRUM toolsets Document as-built architecture and designs within the product description Design data solutions that enable batch, near-real-time, event-driven, and/or streaming approaches depending on business requirements Design & advise on orchestration of data pipeline execution to ensure data products meet customer latency expectations, dependencies are managed, and datasets are as up-to-date as possible, with minimal disruption to end-customer use Ensure that designs are implemented with proper attention to data security, access management.

and data cataloging requirements Approve pull requests related to production deployments Demonstrate solutions to business customers to ensure customer acceptance and solicit feedback to drive iterative improvements Assist in troubleshooting issues for datasets produced by the team (Tier 3 support), on an as-required basis Guide data modelers, business analysts and data scientists in the build of models optimized for KPI delivery, actionable feedback/writeback to operational systems and enhancing the predictability of machine learning models and experiments Develop Bicep or Terraform templates to manage Azure Infra as code Perform hands on data engineering work to build data ingestion and data transformation pipelines Qualifications EDUCATION Requires an extensive knowledge in designing a data model to solve a business problem, specifying a data pipeline design pattern to bring data into a data warehouse, optimizing data structures to achieve required performance, designing low-latency and/or event-driven patterns of data processing, creation of a common data model to support current and future business needs. This knowledge is considered to be normally acquired through the completion of a four year University education in computer science. computer/software engineering or other relevant programs within data engineering, data analysis, artificial intelligence, or machine learning.

EXPERIENCE Experience guiding data lake ingestion and data modeling projects in the Azure cloud environment; experience in modeling relational and in-memory models with star/snowflake schemas; experience with designing and implementing event-driven (pub/sub), near-real-time, or streaming data solutions, involving structured, semi-structured and unstructured data across various platforms and. A period of over 6 years and up to and including 8 years in data modeling, data warehouse design, and data solution architecture in a Big Data environment is considered necessary to gain this experience.