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Data Engineer Jobs in London, ON (NOW HIRING)

Digital Extremes

Principal Data Engineer

London, ON · On-site

CA$115K - CA$125K/yr

ABOUT THIS POSITION We are seeking a Principal Data Engineer with extensive experience in data infrastructure to join our team. Unlike many modern roles that rely entirely on cloud-managed services ...

Digital Extremes

Lead Data Engineer

London, ON

CA$120K - CA$130K/yr

ABOUT THIS POSITION We are seeking a Lead Data Engineer with extensive experience in data infrastructure to join our team. This role serves as a technical leader while also directing the team ...

CARFAX

Senior Director, Data Technology

London, ON · On-site

CA$175K - CA$250K/yr

This senior leader will partner with Product and Engineering leadership to define technology strategy, build a high-performing organization, and unlock greater business value from data. The Role:

StackAdapt

Applied Machine Learning Scientist

London, ON · On-site +1

We are searching for a talented Applied Machine Learning Scientist to join our engineering team as we continue to expand our data science efforts. Our platform is connected to thousands of publishers ...

BDO Canada

Senior Machine Learning Engineer

London, ON

CA$84K - CA$128K/yr

Build and manage scalable data and feature engineering pipelines in Databricks. * Automate model lifecycle processes including training, testing, deployment, and monitoring. * Implement CI/CD ...

BDO Canada

Senior MS Fabric Engineer

London, ON · Hybrid

CA$84K - CA$128K/yr

This net new rolewill contribute to data ingestion, modeling, and reporting efforts using Fabric's data engineering and Power BI capabilities. This is a foundational role as we implement our first ...

Td

Software Engineer II (AI Integration)

London, ON · On-site +1

CA$96K - CA$115K/yr

This role combines software engineering, data science, and machine learning expertise to develop scalable AI systems in production environments. Key Responsibilities * 3-5 years total experince

Td

Software Engineer III (AI Integration)

London, ON · On-site +1

CA$125K - CA$154K/yr

This role combines software engineering, data science, and machine learning expertise to develop scalable AI systems in production environments. Key Responsibilities * Develop end-to-end pipelines ...

AXIS Capital

Associate Data Architect

London, ON

Data and analytics are of critical importance for AXIS. Simply put, we want to turn data into ... developers and other technical experts that will then go forth and build them. Being the ...

Alimentiv

Manager, Clinical Data Management

London, ON · On-site

CA$99K - CA$166K/yr

Serve as the subject matter expert on data collection strategy and handling of study data for assigned programs and effectively liaise with programming to ensure clinical databases are designed in a ...

BDO Canada

AI Engineer

London, ON

CA$77K - CA$117K/yr

Adhere to established AI risk management, data governance, and security policies, and assist with ... Practical experience with DevOps and MLOps practices, including Docker, Kubernetes, and CI/CD ...

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All JobsData Engineer JobsData Engineer Jobs in London, ON

Data Engineer information

See London, ON salary details

$51.8K

$105.8K

$156.2K

How much do data engineer jobs pay per year?

As of Aug 1, 2026, the average yearly pay for data engineer in London, ON is $105,844.00, according to ZipRecruiter salary data. Most workers in this role earn between $84,590.00 and $123,001.00 per year, depending on experience, location, and employer.

Is a data engineer a difficult job?

A data engineer role involves designing, building, and maintaining data pipelines and infrastructure, which requires strong programming skills, knowledge of databases, and familiarity with tools like SQL, Python, and cloud platforms. The job can be challenging due to the complexity of managing large-scale data systems and ensuring data quality and security, but it is manageable with proper training and experience.

What is the difference between Data Engineer vs Data Scientist?

AspectData EngineerData Scientist
Primary FocusBuilding and maintaining data pipelines and infrastructureAnalyzing data to extract insights and create models
SkillsSQL, ETL, programming (Python, Java), database managementStatistics, machine learning, data analysis, programming (Python, R)
Work EnvironmentData warehouses, cloud platforms, backend systemsData analysis environments, research labs, visualization tools
Common ToolsApache Spark, Hadoop, Airflow, SQLJupyter, RStudio, Tableau, scikit-learn

Data Engineers focus on creating and maintaining the infrastructure that allows data to be collected, stored, and processed efficiently. Data Scientists analyze this data to generate insights, build predictive models, and support decision-making. While their skills overlap, Data Engineers are more involved in data pipeline development, whereas Data Scientists focus on data analysis and modeling.

What are the key skills and qualifications needed to thrive as a Data Engineer, and why are they important?

To thrive as a Data Engineer, you need a strong background in computer science, data modeling, and programming languages such as Python or Java, often coupled with a relevant degree. Familiarity with ETL tools, big data frameworks (like Hadoop or Spark), and cloud platforms (such as AWS or Azure) is typically required, along with certifications like AWS Certified Data Analytics. Strong problem-solving skills, attention to detail, and effective communication set exceptional data engineers apart. These skills and qualities are essential for building robust data pipelines, ensuring data quality, and supporting data-driven decision-making across organizations.

What Does a Data Engineer Do?

The job duties of a data engineer involve helping with the development of systems, software, and infrastructure used to process, store and analyze data. Your responsibilities in this career include working to install data management software. Your employer may expect you to perform maintenance and install updates to all software and systems that they use for data acquisition, management, and analysis. Data engineers also analyze existing data systems to find ways to improve efficiency and accessibility. You then suggest upgrades or changes based on your assessment.

What are Data Engineers?

Data Engineers are IT professionals who design, construct, install, and maintain large-scale processing systems and other infrastructure for collecting, storing, and analyzing data. They build and optimize data pipelines and architectures that allow organizations to efficiently access and use data for business insights. Data Engineers work closely with data scientists, analysts, and other stakeholders to ensure that data is reliable, accessible, and secure. Their responsibilities often include working with databases, cloud platforms, and big data tools.

How do Data Engineers typically collaborate with Data Scientists and Analysts within an organization?

Data Engineers play a crucial role in ensuring that Data Scientists and Analysts have reliable, well-structured data for their projects. This collaboration often involves building and maintaining data pipelines, optimizing data storage solutions, and troubleshooting data quality issues. Regular communication and agile teamwork are common, with Data Engineers frequently participating in meetings to understand analytical requirements and adjust data processes accordingly. By working closely together, these teams can quickly iterate on data models and deliver actionable insights to drive business decisions.

What does a data engineer actually do?

A data engineer designs, builds, and maintains the infrastructure and pipelines that enable organizations to collect, store, and process large volumes of data. They work with tools like SQL, Python, and cloud platforms to ensure data is accessible, reliable, and ready for analysis by data scientists and analysts.

Is a data engineer entry level?

Data engineering is typically an intermediate to senior role that requires experience with programming, databases, and data pipelines. Entry-level positions may be available for those with relevant internships, certifications, or strong foundational skills in SQL, Python, or cloud platforms, but most roles expect prior experience or demonstrated technical competence.

What engineer makes $500,000 a year?

Senior data engineers with extensive experience, advanced skills in big data tools, and certifications can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or within large tech companies. Such compensation often includes bonuses, stock options, and other incentives. These roles typically require strong programming, cloud platform expertise, and a deep understanding of data architecture.
More about Data Engineer jobs
What are the most commonly searched types of Data Engineer jobs in London, ON? The most popular types of Data Engineer jobs in London, ON are:
What job categories do people searching Data Engineer jobs in London, ON look for? The top searched job categories for Data Engineer jobs in London, ON are:
What cities near London, ON are hiring for Data Engineer jobs? Cities near London, ON with the most Data Engineer job openings:
Data Engineer jobs near you
Infographic showing various Data Engineer job openings in London, ON as of July 2026, with employment types broken down into 72% Full Time, and 28% Contract. Highlights an 100% In-person job distribution, with an average salary of $105,844 per year, or $50.9 per hour.

Principal Data Engineer

Digital Extremes

London, ON • On-site

CA$115K - CA$125K/yr

Other

Re-posted 14 days ago

Job description

ABOUT THIS POSITION

We are seeking a Principal Data Engineer with extensive experience in data infrastructure to join our team. Unlike many modern roles that rely entirely on cloud-managed services, this position is looking for someone to manage our self-hosted and on-premise data stacks.

We need a proactive, solutions-oriented engineer who can rapidly master our current self-hosted systems, identify performance bottlenecks, and design our future infrastructure to adapt to the company needs. In this role, you will own the technical architecture, set engineering standards, and translate complex business requirements into reliable, scalable data systems. 

RESPONSIBILITIES
  • Infrastructure Strategy & Ownership: Manage and optimize self-hosted database and data warehousing solutions. Oversee performance tuning, hardware planning, and OS-level monitoring for large-scale data systems. 
  • Pipeline Architecture: Design, develop, and maintain robust ETL/ELT pipelines for data ingestion and processing from varied, complex data sources.
  • Technical Execution: Drive large-scale technical projects from design to delivery, making key architectural decisions and managing technical risk.
  • Engineering Standards: Establish code and architecture review standards, championing engineering best practices across the team. 
  • Data Governance & Security: Ensure infrastructure and pipelines strictly comply with government policies, data privacy, and GDPR regulations.
  • Collaboration: Partner with data scientists, analysts, and business stakeholders to translate complex data requirements into scalable infrastructure.
REQUIREMENTS
  • Experience: 5+ years of professional experience in data engineering, database administration, or backend infrastructure, with a strong, proven focus on managing self-hosted/on-premise environments rather than exclusively cloud-managed services.
  • Deep Database Foundations: Extensive hands-on experience managing and optimizing database management systems, specifically PostgreSQL and MongoDB (both relational and NoSQL ecosystems).
  • Self-Hosted Mastery: Proven experience setting up, maintaining, and tuning self-hosted/on-premise databases and data warehouses.
  • System Environment: Strong proficiency in SQL and deep comfort working within Linux/Unix environments (command line, shell scripting, system performance tuning).
  • Data Orchestration: Hands-on experience with modern ETL orchestration tools such as Dagster or Airflow.
  • Data Modeling: In-depth knowledge of core data warehousing concepts and relational data modeling.
  • Technical Ownership: Proven track record of owning complex technical systems, driving implementation, and ensuring architectural standards are met.
  • Communication: Ability to clearly communicate technical decisions, trade-offs, and infrastructure constraints to both engineering teams and non-technical stakeholders. 

 "Applicants must be legally eligible to work in Canada at the time of application."

Please note that the salary range mentioned in this job description should serve simply as a guide. The final compensation offered may vary based on a variety of factors, including bonuses and/or incentives, or a candidate's experience, skills, budget and location. Digital Extremes is committed to providing a fair, equitable, and competitive package that reflects the value a candidate brings.

Salary Range: $115,000 - $125,000

Existing Vacancy: Yes - we're currently hiring candidates for an existing vacancy in this position

We believe in the power of human connection. At Digital Extremes, we do not use artificial intelligence (AI) to screen, assess, or select candidates. All applications are reviewed by human, qualified recruiters.

During your interview, our recruitment team will leverage  Gemini as a note-taker only. At Digital Extremes, a core value of our studio is that we do not leverage AI in any of our development processes; this is a strict company policy.  Please note that we permit the use of AI tools exclusively for administrative support, it is not used for candidate selection, screening, or any part of the decision-making process. All evaluations are conducted solely by our team to ensure our hiring remains a human-led process, just as our development remains the work of our artists and creators.  

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