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

I-cube Software Llc

Data Engineer

Toronto, ON · Remote

CA$35 - CA$55/hr

Hybrid Hadoop Engineer and Hadoop Infrastructure Administrator to build and maintain a scalable and resilient Big Data framework to support Data Scientists. As an administrator, your responsibility ...

Clio

Senior Developer, Enterprise AI

Toronto, ON · Remote

CA$157K - CA$212K/yr

Bachelor's degree in Computer Science, Engineering, Data, or equivalent practical experience. * Demonstrate a keen interest in improving your craft by using AI. This is a new position. #LI-Remote ...

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 ...

Morson Talent

25-153 BI Developer

Oshawa, ON · Remote

$60 - $85/hr

Oshawa, ON (100% remote) Job Overview JOB FUNCTIONS: Semantic Modeling & Enterprise Reporting is ... Experience collaborating with data engineering, governance, and business teams in a cross ...

Rush Street Interactive

Senior Server Engineer

Toronto, ON · Remote

CA$124K - CA$186K/yr

... Data Engineering, Infrastructure, and the Engineering team. You'll help shape the technical ... Ability to travel occasionally, both domestically and internationally #LI-REMOTE #LI-PROMOTE This ...

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Remote Data Engineering information

What is remote data engineering?

Remote data engineering involves designing, building, and maintaining data systems and pipelines while working from a location outside of a traditional office. Remote data engineers use tools to collect, process, and store large sets of data, making it accessible for analysis and business decision-making. They collaborate with teams virtually, often using cloud-based technologies, to ensure that data infrastructure is reliable, scalable, and secure. This role requires strong technical skills in programming, databases, and data architecture, as well as the ability to communicate effectively in a distributed work environment.

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

To thrive as a Remote Data Engineer, you need strong programming skills (such as Python, Java, or Scala), experience with data modeling, ETL processes, and a solid understanding of database systems, often supported by a degree in computer science or a related field. Proficiency with big data tools like Apache Spark, Hadoop, cloud platforms (AWS, Azure, GCP), and certifications in these technologies is highly valued. Excellent problem-solving abilities, self-motivation, and clear communication are crucial soft skills for remote collaboration and project delivery. These competencies ensure effective data pipeline development, reliable data management, and seamless teamwork across distributed environments.

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

Remote data engineers often work with distributed teams, which requires strong communication and organization skills. They collaborate using tools like Slack, Zoom, and project management platforms to stay aligned on data pipeline development, troubleshooting, and deployment. Regular stand-ups, asynchronous documentation, and clear communication of progress are essential for ensuring everyone is on the same page, regardless of location. Flexibility in working hours and proactive scheduling of meetings help facilitate effective collaboration and project delivery.

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

AspectRemote Data EngineeringRemote Data Analyst
Required CredentialsBachelor's in CS, Data Science, or related field; experience with SQL, Python, cloud platformsBachelor's in Statistics, Data Science, or related; proficiency in Excel, SQL, visualization tools
Work EnvironmentBuilds data pipelines, manages databases, works with cloud infrastructureAnalyzes data sets, creates reports, visualizes data insights
Employer & Industry UsageTech companies, finance, healthcare, e-commerceMarketing agencies, finance, retail, consulting

Remote Data Engineering focuses on designing and maintaining data infrastructure, while Remote Data Analysts interpret data to provide insights. Both roles require strong analytical skills but differ in technical depth and responsibilities.

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

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

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

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

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

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

Remote Data Engineering jobs near you
Infographic showing various Remote Data Engineering job openings in Toronto, ON as of July 2026, with employment types broken down into 1% As Needed, 81% Full Time, 9% Part Time, and 9% Contract. Highlights an 81% Physical, 3% Hybrid, and 16% Remote job distribution.

Data Engineer

I-cube Software Llc

Toronto, ON • Remote

CA$35 - CA$55/hr

Part-time

Re-posted 12 days ago

Job description

Hybrid Hadoop Engineer and Hadoop Infrastructure Administrator to build and maintain a scalable and resilient Big Data framework to support Data Scientists. As an administrator, your responsibility will be to deploy and maintain Hadoop clusters, add and remove nodes using cluster management and monitoring tools like Cloudera Manager, and support performance and scalability requirements, in support of our Data scientist's needs. Some Relational Database administrator experience will also be desirable to support the general administration of Relational Databases.

Design, build, and maintain Big Data workflows/pipelines to process a continuous stream of data with experience in end-to-end design and build process of Near-Real-Time and Batch Data Pipelines.


Demonstrated work experience in the following with Big Data and distributed programming models and technologies
Knowledge of database structures, theories, principles, and practices (both SQL and NoSQL).
Active development of ETL processes using Spark or other highly parallel technologies, and implementing ETL/data pipelines
Experience with Data technologies and Big Data tools, like Spark, Kafka, Hive
Understanding of Map Reduce and other Data Query and Processing and aggregation models
Understanding of challenges of transforming data across distributed clustered environment
Experience with techniques for consuming, holding, and aging out continuous data streams
Ability to provide quick ingestion tools and corresponding access APIs for continuously changing data schema, working closely with Data Engineers around specific transformation and access needs

Preferred:

Experience as a Database administrator (DBA) will be responsible for keeping critical tools database up and running
Building and managing high-availability environments for databases and HDFS systems
Familiarity with transaction recovery techniques and DB Backup

Skills and Attributes:

Ability to have effective working relationships with all functional units of the organization
Excellent written, verbal, and presentation skills
Excellent interpersonal skills
Ability to work as part of a cross-cultural team
Self-starter and Self-motivated
Ability to work without lots of supervision
Works under pressure and is able to manage competing priorities.

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