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Remote Startup Data Engineer Jobs in Toronto, ON

It's also why the majority of our roles are remote-first, meaning you can work from anywhere you ... You'll work at the intersection of data engineering, business intelligence, finance analytics ...

It's also why the majority of our roles are remote-first, meaning you can work from anywhere you ... You'll work at the intersection of data engineering, business intelligence, finance analytics ...

MP5 Hourly Rate: $80 - $95/hour Duration: 10 Months Hours of work: 35 Location: 889 Brock Rd., Pickering (100% Remote) Job Overview JOB FUNCTION As a Senior Data Developer, you will be responsible ...

... Data Theorem's engineering team, which is spread across the United States, England, France, and Canada. * Be amazed at your opportunity for growth within a top cybersecurity startup. We're looking ...

Senior Manager, Data Engineering

Toronto, ON ยท On-site +1

CA$142K - CA$177K/yr

You will be based in our Toronto office, balancing in-office collaboration with remote flexibility. Reporting Relationship : You will report to the Director, Data Engineering Posting Type

Senior AI Engineer - Remote

Toronto, ON ยท On-site +1

CA$147K - CA$245K/yr

Req ID: 369008 NTT DATA strives to hire exceptional, innovative and passionate individuals who want ... We are currently seeking a Senior AI Engineer - Remote to join our team in Toronto, Ontario (CA-ON ...

Senior Machine Learning Engineer

Toronto, ON ยท Remote

$165K - $225K/yr

... remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus ... data engineering, data governance, and data quality across research and production pipelines ...

Senior Machine Learning Engineer

Toronto, ON ยท Remote

$165K - $225K/yr

... remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus ... data engineering, data governance, and data quality across research and production pipelines ...

25-026 DevOps Engineer

Toronto, ON ยท 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 ...

This is a remote role overseeing a team of 2 and reporting to the Sr. Director of Data Engineering. Responsibilities: * Champion data literacy: Provide ongoing training and support to the Engagement ...

Senior ML Engineer

Toronto, ON ยท Remote

$180K - $240K/yr

You're an applied AI engineer who thrives in startup environments, writes clean Python, and can ... Remote-first with strong perks -- flexible vacation, paid sabbatical after 5 years, comprehensive ...

Senior Infrastructure Engineer

Toronto, ON ยท Remote

CA$170K - CA$220K/yr

Remote - Remote - Based In ET+2 / -3, NY Preferred Remote | Full-time Compensation: $170K - $220K ... Engagement with a fast-moving, well-funded startup during a period of high growth. * Inclusive ...

Senior ML Engineer

Toronto, ON ยท Remote

$180K - $240K/yr

You're an applied AI engineer who thrives in startup environments, writes clean Python, and can ... Remote-first with strong perks -- flexible vacation, paid sabbatical after 5 years, comprehensive ...

Vancouver, BC preferred, considering the rest of Canada (Remote-friendly) Industry: Web3 ... Company Overview Our client is a fast-growing Web3 fintech startup headquartered in Vancouver ...

Showing results 21-40

Remote Startup Data Engineer information

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

AspectRemote Startup Data EngineerRemote Startup Data Analyst
Required CredentialsBachelor's in CS, Data Engineering certificationsBachelor's in Statistics, Data Analysis certifications
Work EnvironmentBuilding data pipelines, infrastructureInterpreting data, creating reports
Employer & Industry UsageTech startups, SaaS companiesMarketing agencies, e-commerce startups
Common Search & ComparisonOften compared for technical depth and infrastructure focusCompared for data interpretation and business insights

The main difference between a Remote Startup Data Engineer and a Remote Startup Data Analyst lies in their focus areas. Data Engineers build and maintain data infrastructure, while Data Analysts interpret data to inform business decisions. Both roles are essential in startups but require different skill sets and responsibilities.

What are the most commonly searched types of Startup Data Engineer jobs in Toronto, ON? The most popular types of Startup Data Engineer jobs in Toronto, ON are:
What are popular job titles related to Remote Startup Data Engineer jobs in Toronto, ON? For Remote Startup Data Engineer jobs in Toronto, ON, the most frequently searched job titles are:
What job categories do people searching Remote Startup Data Engineer jobs in Toronto, ON look for? The top searched job categories for Remote Startup Data Engineer jobs in Toronto, ON are:
Infographic showing various Remote Startup Data Engineer job openings in Toronto, ON as of August 2026, with employment types broken down into 1% As Needed, 66% Full Time, 30% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Data Platform Engineer

Tucows

Toronto, ON โ€ข Remote

Full-time

Re-posted 20 hours ago


Job description

Tucows (NASDAQ:TCX, TSX:TC) is possibly the biggest Internet company you've never heard of. We started as a simple shareware site in 1993 and have since grown into a stable of businesses: Tucows Domains, Ting Internet and Wavelo.

We embrace a people-first philosophy that is rooted in respect, trust, and flexibility. We believe that whatever works for our employees is what works best for us. It's also why the majority of our roles are remote-first, meaning you can work from anywhere you can connect to the Internet!

Today, over one thousand people work in over 20 countries to help us make the Internet better. If this sounds exciting to you, join the herd!

About the Role

We're looking for a curious, technically strong, and automation-minded Data Platform Engineer to join our Data Engineering team. This is a high-impact platform engineering role for someone who enjoys building reliable systems, writing maintainable automation, and helping data teams move faster, more safely, and with more confidence.

You'll work at the intersection of data engineering, business intelligence, finance analytics, cloud infrastructure, governance, and AI-enabled decision support. What we're really hiring for is strong engineering fundamentals, comfort with ambiguity, and the drive to apply those fundamentals across different systems.

We're hiring an engineer who can pick up infrastructure work, governance work, or pipeline work as needed and help turn knowledge that currently lives in repos, configs, and people's heads into durable platform practices. There will be a lot to learn here, even if you arrive experienced. That's the appeal, not the catch.

What You'll Do

Keep the data platform healthy: Monitor infrastructure and pipelines, respond to issues, troubleshoot failures from logs and metrics, and help identify root causes so we can prevent repeat problems.

Make infrastructure changes safely: Build, review, and deploy infrastructure through code using Terraform, AWS, Kubernetes or container-based deployment patterns, and CI/CD workflows.

Improve automation and tooling: Write Python, bash, and CI/CD automation that reduces manual toil, improves reliability, and makes common platform tasks safer and easier for the team.

Support access control and governance: Help design and operate role-based access control, least-privilege access, and governance controls across our cloud, warehouse, and BI platforms.

Contribute to data pipelines: Build, operate, and troubleshoot pipelines and transformations that power reporting, analytics, finance workflows, and data products across the company.

Support our platform migration: Help move workloads from our legacy stack to the modern data platform, including validation, cutover, and decommissioning work.

Document how things work: Write clear runbooks, platform documentation, and operational guides so knowledge is easier to share and the team is less dependent on any one person.

Use and improve AI-assisted engineering: Work with our Claude Code-based tooling, including agents, skills, hooks, and MCP integrations, and help shape how the team uses AI to improve engineering workflows.

What We're Looking For

Experience: 3+ years in data engineering, software engineering, DevOps, platform engineering, or a related technical role.

Cloud and DevOps fundamentals: Hands-on experience operating workloads in AWS or another major cloud provider, with a solid grasp of IAM, networking, compute, managed services, deployment patterns, and day-to-day cloud operations.

Python automation: Proficiency in Python for automation, internal tooling, platform workflows, or data engineering support.

SQL competency: Working knowledge of SQL. Advanced SQL is a plus, but not a prerequisite.

Infrastructure as Code: Hands-on experience with Terraform or another infrastructure-as-code tool, including code review, state-aware changes, environment management, and safe deployment practices.

CI/CD and Git workflows: Comfortable using Git-based development workflows, pull requests, automated testing, and CI/CD pipelines to ship changes safely.

Kubernetes and containerized workloads: Good working knowledge of Kubernetes and container-based deployments. You should be comfortable understanding deployments, pods, services, logs, configuration, and common failure modes. Experience with EKS is especially valuable.

Observability, Debugging and Operations: Skilled at using logs, metrics, and alerts to investigate failing systems, reason through incomplete information, and identify likely root causes.

Access control and governance mindset: Familiarity with RBAC, IAM, least-privilege access, or governance controls in at least one platform — cloud, warehouse, BI, or application-level systems.

Strong fundamentals and learning mindset: Attention to detail, curiosity, good judgment, and genuine eagerness to learn unfamiliar tools and systems.

Vendor & Incident Management: Experience working with vendor support, production incidents, severity-based escalation, and operational follow-through.

Operational Ownership: Willingness to participate in on-call and after-hours support as needed. You understand that reliable platforms require thoughtful operations, not just build work.

Remote collaboration: Clear written communication and the ability to work effectively with engineers, analysts, and data stakeholders in a remote-first team.

Our Broader Stack

Cloud & Infrastructure: AWS, GCP, OpenStack, Terraform, Docker, Kubernetes, Helm
Data Platform: Snowflake, BigQuery, dbt, Airflow/MWAA, Kafka, DataHub
Ingestion & Legacy Systems: Fivetran, Stitch, Pentaho Data Integration
Observability: Prometheus, Grafana, CloudWatch
BI & Development Workflow: Looker, GitHub, Claude Code

​​The base salary range for this position is $90,700 - $113,400. Range shown in $CAD for Canadian residents. Other countries will differ. Range may vary on a number of factors including, but not limited to: location, experience and qualifications. Tucows believes in a total rewards offering that includes fair compensation and generous bene

Experience with these tools is a plus, what matters most is that you bring strong engineering fundamentals, sound operational judgment, and the ability to learn quickly.

Want to know more about what we stand for? At Tucows we care about protecting the open Internet, narrowing the digital divide, and supporting fairness and equality.

We also know that diversity drives innovation. We are committed to inclusion across race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status or disability status. We celebrate multiple approaches and diverse points of view.

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request an accommodation.

We use AI-enabled tools throughout our recruitment process to help us work more efficiently and consistently. These tools support our hiring teams by organizing and reviewing information, while final hiring decisions are always made by people.

Tucows and its subsidiaries participate in the E-verify program for all US employees.

Learn more about Tucows, our businesses, culture and employee benefits on our site here.