IT & data jobs in Canada

Explore it & data jobs in Canada. Choose a role or place to find work that fits.

Counted Sep 21, 2026

Hiring at a glance

View jobs

Open jobs: 2,617
Employers: 1,276

Advertised starting pay

Average starting payCAD / year: $98,481Across 247 listings
Average starting payCAD / hour: $48.31Across 83 listings
Average starting payUSD / year: $119,163Across 55 listings
Average starting payUSD / hour: $57.29Across 11 listings

Employer-advertised starting pay, not employee salaries. Currencies and pay periods stay separate.

Where work happens

Remote: 5%125 listings
Hybrid: 39%1,018 listings
On-site: 56%1,454 listings

Not specified: 1% (20 listings)

Employers hiring include RBC (63), Royal Bank of Canada (47), TD (45).

Sources & calculation notes

These figures describe the listings on this role page at the date shown, not the whole job market. Listings can change.

Employer-listed minimums from at least 10 listings per currency and pay period. These are advertised starting amounts, not employee salaries. Jobs without a minimum and unusual amounts are excluded.

Hybrid and on-site classifications may be inferred from descriptions. Check the original ad. How we count

IT & data jobs in Canada

Save this search

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Toronto, ON
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Toronto, ON
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Contract

RBC

Senior Data Engineer

Toronto, ON, Canada

Job type: Full-time
Apply by: Oct 2, 2026
Experience: 3+ years of hands-on data engineering experience.
Posting language: English
Posted: Sep 17, 2026

Apply About employer

Applications open in a new tab.

Original job description

Job Description

WHAT IS THE OPPORTUNITY?

We are seeking a Lead Data Engineer to build and maintain scalable data pipelines supporting analytics and reporting. The engineer will follow end-to-end process standards and guidelines to ensure accurate and efficient build out of data pipeline architecture within project timeframes.

WHAT WILL YOU DO?

Design, implement and maintain data ingestion and transformation pipelines.
Build transformation models and data pipelines using dbt.
Develop optimized SQL transformations for large datasets.
Implement data quality checks and validation logic within ETL pipelines.
Monitor data pipelines and troubleshoot production issues.
Collaborate with data analysts and architects to design scalable data models.
Document data lineage, transformations, and technical architecture.
Participate in Agile development processes and code reviews.

WHAT DO YOU NEED TO SUCCEED?

Must have:

3+ years of hands-on data engineering experience.
Strong technical proficiency in:
- Python: Production-quality code for data pipelines, automation, and scripting, including PySpark.
- SQL: Advanced query writing, optimization, indexing, stored procedures.
- ETL: Utilizing DataFrames for building programmatic ETL data pipelines.
- AWS: S3, Glue, Lambda, Redshift, Cloudwatch.
- Snowflake: Data warehousing, virtual warehouses, clustering, security.
- dbt: Model development, testing, documentation, incremental builds.
Familiarity with data orchestration tools (Airflow).
Demonstrated ability to work independently, take ownership, and drive projects to completion.
Excellent problem-solving skills and attention to detail.

Nice-to-have:

Knowledge of data streaming platforms or queues (Apache Kafka, AWS Kinesis, RabbitMQ)
Experience in building Kotlin, Spring boot and Java applications.
Familiarity with Parquet formatting to maximize I/O performance and storage efficiency across data lakes.

What’s in it for you?

We thrive on the challenge to be our best, progressive thinking to keep growing, and working together to deliver trusted advice to help our clients thrive and communities prosper. We care about each other, reaching our potential, making a difference to our communities, and achieving success that is mutual.

A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock where applicable
Leaders who support your development through coaching and managing opportunities
Ability to make a difference and lasting impact
Work in a dynamic, collaborative, progressive, and high-performing team
A world-class training program in financial services
Flexible work/life balance options
Opportunities to do challenging work

Job Skills

Big Data Management, Cloud Computing, Database Development, Data Mining, Data Warehousing (DW), ETL Processing, Group Problem Solving, Quality Management, Requirements Analysis

Additional Job Details

Address:

20 KING ST W:TORONTO

City:

Toronto

Country:

Canada

Work hours/week:

37.5

Employment Type:

Full time

Platform:

TECHNOLOGY AND OPERATIONS

Job Type:

Regular

Pay Type:

Salaried

Posted Date:

2026-09-17

Application Deadline:

2026-10-02

Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above

Our Employment Opportunities

At RBC, we are guided by living shared values of Client First, Integrity, Collaboration, Respect and Excellence and winning together as One RBC. We believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.

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Expand your limits and create a new future together at RBC. Find out how we use our passion and drive to enhance the well-being of our clients and communities at jobs.rbc.com.

RBC is presently inviting candidates to apply for this existing vacancy. Applying to this posting allows you to express your interest in this current career opportunity at RBC. Qualified applicants may be contacted to review their resume in more detail.

Apply About employer

More about this job

Responsibilities

The Lead Data Engineer will design, implement, and maintain scalable data ingestion and transformation pipelines using tools like dbt and Python. They will also collaborate with architects to build data models and ensure data quality through rigorous validation and monitoring.

Requirements

Candidates must have at least 3 years of hands-on data engineering experience with proficiency in Python, SQL, and AWS cloud services. Strong technical skills in Snowflake, ETL processes, and data orchestration are essential for success in this role.

Skills

Python
PySpark
SQL
ETL
AWS
S3
Glue
Lambda
Redshift
Snowflake
dbt
Airflow
Data engineering
Data modeling
Data pipelines
Agile

Benefits

Bonuses
Flexible benefits
Competitive compensation
Commissions
Stock options
Professional development coaching
Training program
Flexible work-life balance

Visa sponsorship

Not detected in the job text

Keywords

Data Engineering
Python
PySpark
SQL
ETL
AWS
S3
Glue
Lambda
Redshift
Cloudwatch
Snowflake
dbt
Airflow
Data Pipelines
Data Modeling
Agile
Kafka
Kinesis
RabbitMQ
Kotlin
Spring Boot
Java
Parquet
Big Data Management
Cloud Computing
Database Development
Data Warehousing
Quality Management
Requirements Analysis

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