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1,035

Data Engineer jobs in Canada

Senior Data Engineer, Corporate Data and Analytics

Lyft

Toronto
On-site
CAD 136,000 - 170,000
30+ days ago
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Data Engineer

Manulife

Southwestern Ontario
On-site
CAD 94,000 - 175,000
30+ days ago

Data Engineer

Medium

Toronto
On-site
CAD 80,000 - 110,000
30+ days ago

Data Engineer

Nexus Systems Group Inc.

Mississauga
Hybrid
CAD 100,000 - 120,000
30+ days ago

Data Engineer

Global Spatial Technology Solutions (GSTS)

Dartmouth
On-site
CAD 80,000 - 100,000
30+ days ago
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Senior Data Engineer - GFT

RBC

Toronto
On-site
CAD 80,000 - 100,000
30+ days ago

AWS Data Engineer

Virtusa

Toronto
On-site
CAD 100,000 - 120,000
30+ days ago

Senior Data Engineer

Afresh

Canada
On-site
CAD 142,000 - 170,000
30+ days ago
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Data Engineer (Hybrid)

Homebase

Toronto
On-site
CAD 80,000 - 100,000
30+ days ago

Senior Data Engineer (ML/AI)

GuruLink

Vancouver
On-site
CAD 80,000 - 100,000
30+ days ago

data engineer

Clientserver Tech Systems

Mississauga
On-site
CAD 60,000 - 80,000
30+ days ago

Senior DataOps & Cloud Data Engineer

Rubicon Path

Toronto
On-site
CAD 100,000 - 130,000
30+ days ago

Principal Data Engineer - Tangerine

Scotiabank

Toronto
On-site
CAD 110,000 - 150,000
30+ days ago

Principal Data Engineer: Real-Time Data & AI Leader

PointClickCare

Mississauga
Hybrid
CAD 220,000 - 246,000
30+ days ago

Senior Software Engineer, Data Pipelines

Lyft

Toronto
On-site
CAD 136,000 - 170,000
30+ days ago

Senior Frontend Engineer, Data Browsing

Sentry.io

Toronto
Hybrid
CAD 206,000 - 288,000
30+ days ago

Data Engineer: Petabyte-Scale Pipelines on AWS (Python)

HRB

Canada
Remote
CAD 80,000 - 120,000
30+ days ago

Hybrid Data Engineer - Snowflake & Real-Time Pipelines

PSYCHO BUNNY

Montreal
Hybrid
CAD 80,000 - 120,000
30+ days ago

Senior Fullstack Engineer, Data Browsing

Sentry

Toronto
On-site
CAD 206,000 - 288,000
30+ days ago

Senior Fullstack Engineer, Data Browsing

Sentry.io

Toronto
Hybrid
CAD 206,000 - 288,000
30+ days ago

Lead Data Engineer: GCP & Big Data Pipelines

Scotiabank

Toronto
On-site
CAD 120,000 - 150,000
30+ days ago

Data Engineer, Pretraining Data — Remote-Friendly

Cohere

Toronto
Hybrid
CAD 80,000 - 100,000
30+ days ago

Senior Data Engineer — Scale ETLs with PySpark & Databricks

Afresh

Canada
On-site
CAD 142,000 - 170,000
30+ days ago

Senior Data Engineer — Fraud & AML Data Pipelines

RBC

Toronto
On-site
CAD 80,000 - 100,000
30+ days ago

Data Engineer: Scale Pipelines, BI & Cloud Data

Medium

Toronto
On-site
CAD 80,000 - 110,000
30+ days ago

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Senior Data Engineer, Corporate Data and Analytics
Lyft
Toronto
On-site
CAD 136,000 - 170,000
Full time
30+ days ago

Job summary

A leading transportation company in Toronto is looking for a Senior Data Engineer to lead the design and operation of critical data systems. Responsibilities include mentoring junior engineers and driving data quality across teams. Ideal candidates have 5+ years of experience, strong Python and SQL skills, and a background in cloud technology. This role offers a hybrid work environment and competitive compensation ranging from CAD $136,000 to CAD $170,000.

Benefits

Health and dental coverage
Mental health benefits
Family building benefits
Child care and pet benefits
RRSP plan

Qualifications

  • 5+ years of experience in data engineering and data platforms.
  • Expert-level proficiency in Python and SQL.
  • Deep understanding of analytic and data needs within companies.

Responsibilities

  • Lead the design and operation of data systems and pipelines.
  • Mentor junior engineers on data engineering best practices.
  • Implement frameworks for automating data management.

Skills

Data engineering
Python proficiency
SQL proficiency
Cloud technologies
Mentoring engineers
CI/CD practices

Tools

Apache Airflow
AWS
Databricks
Snowflake
Job description

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

We believe that our data is one of our greatest assets, and the insights we derive from it are crucial to our success. The Corporate Data and Analytics team’s mission is to enable trusted Analytics, Data Science, and AI for all Corporate functions, including Finance, Marketing, People, and Enterprise.

As a SeniorData Engineer, you will be a key technical leader on the team, owning the design, development, and operation of our critical data systems. You will drive engineering and operational excellence across the team, ensuring our data assets are high-quality, secure, and accessible for a variety of use cases.

Responsibilities:
  • Leadership & System Ownership
    • Lead the design, development, and operation of key data systems and pipelines, taking full ownership from ideation to production.
    • Mentor junior engineers on best practices for data engineering, testing, and operational excellence.
    • Drive collaboration with cross-functional partners (Product, Analytics, Data Science, and Business) to align on data needs and project priorities and deliver reliable data workflows
  • Engineering & Operational Excellence
    • Architect and build scalable batch and real-time data pipelines, ensuring data quality, security, and governance using Apache Airflow 2.0 and Astronomer.
    • Lead architectural reviews and propose improvements to reduce complexity and operational burden.
    • Drive post-incident investigations and lead efforts to resolve challenging issues and complete all resulting action items.
    • Champion investments in architecture, observability, performance, and tooling to improve our systems and processes.
    • Develop and optimize DAGs for reliability, performance, and maintainability.
  • Planning & Execution
    • Propose new projects and assist in prioritization, leveraging your deep understanding of the business and data needs.
    • Break down complex work into manageable features and milestones, aligning dependencies for seamless execution.
    • Deliver high-quality code and provide actionable, constructive feedback in code reviews.
    • Create and promote thorough documentation of systems, designs, and processes to support knowledge sharing and onboarding.
Experience:
  • Required
    • 5+ years of experience in data engineering and data platforms, particularly with cloud technologies like AWS, Databricks, and Snowflake.
    • Expert-level proficiency in Python and SQL.
    • Extensive experience with big data compute and storage technologies (e.g., Spark, Trino, Hive, Cloud Storage).
    • Proven ability to apply full-scale software development practices to data, including test automation, CI/CD, and DevOps.
    • Deep understanding of analytic and data needs within corporate functions like Finance, Marketing, Sales, and People.
    • Expertise in creating and implementing frameworks and APIs for automating data management and governance.
    • Track record of mentoring and leading other engineers, driving project execution, and collaborating with cross-functional partners.
  • Preferred
    • Experience with Graph databases, Vector databases, and Conversational analytics.
    • Background in building Agentic applications for data engineering and operations.
Benefits:
  • Extended health and dental coverage options, along with life insurance and disability benefits
  • Mental health benefits
  • Family building benefits
  • Child care and pet benefits
  • Access to a Lyft funded Health Care Savings Account
  • RRSP plan to help save for your future
  • In addition to provincial observed holidays, salaried team members are covered under Lyft's flexible paid time off policy. The policy allows team members to take off as much time as they need (with manager approval). Hourly team members get 15 days paid time off, with an additional day for each year of service
  • Lyft is proud to support new parents with 18 weeks of paid time off, designed as a top-up plan to complement provincial programs. Biological, adoptive, and foster parents are all eligible.
  • Subsidized commuter benefits

Lyft is committed to creating an inclusive workforce that fosters belonging. Lyft believes that every person has a right to equal employment opportunities without discrimination because of race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, gender identity, gender expression, age, marital status, family status, disability, pardoned record of offences, or any other basis protected by applicable law or by Company policy. Lyft also strives for a healthy and safe workplace and strictly prohibits harassment of any kind. Accommodation for persons with disabilities will be provided upon request in accordance with applicable law during the application and hiring process. Please contact your recruiter if you wish to make such a request.

Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule — Team Members will be expected to work in the office at least 3 days per week, including on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid

The expected base pay range for this position in the Toronto area is CAD $136,000 - CAD $170,000. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Range is not inclusive of potential equity offering, bonus or benefits. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.

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* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.

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