Data engineer jobs in Canada (801 jobs)

Find data engineer jobs across Canada. Choose a place, compare current openings and read the employer’s requirements.

Counted Nov 6, 2026

Hiring at a glance

View jobs

Open jobs: 801
Employers: 392

Advertised starting pay

Average starting payCAD / year: $103,171Across 89 listings
Average starting payCAD / hour: $63.78Across 36 listings

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

Where work happens

Remote: 4%33 listings
Hybrid: 40%317 listings
On-site: 56%447 listings

Not specified: <1% (4 listings)

Employers hiring include S M Software Solutions Inc (29), Capgemini (27), J&M Group (15).

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

Data engineer jobs in Canada

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Added 2 months ago
RB
Senior Data Engineer
Royal Bank of Canada
Vancouver, BC
- Full-time
In this role as a Senior Data Engineer, you will be responsible for development deliverables for the Finance Data Platform. The Platform, leverages Airflow and Databricks and serves as the…
Added 2 months ago
B
Data Engineer - Sports & Prediction Markets
Betstamp
Toronto, ON
- Full-time
Added 2 months ago
B
Market Data Engineer - Prediction Markets & Odds Infrastructure
Betstamp
Toronto, ON
- Full-time
Added 2 months ago
V
Sr Data Engineer, Specialist
Vanguard
Toronto, ON
- Full-time
We are looking for a Sr Data Engineer with in-depth expertise in AWS, Databricks, and modern data
Added 2 months ago
S
Senior Data Engineer
Super.com
Remote, Canada
- Full-time
- Remote
Added 2 months ago
Senior Data Engineer - Vancouver
Capgemini
Vancouver, BC
We are seeking a highly experienced Senior Data Engineering Lead w
Added 2 months ago
Google Cloud Platform (GCP) Data Engineer
Capgemini
Toronto, ON
Google Cloud Platform (GCP) Data Engineer with hands-on experience with Google Cloud Platform
Added 2 months ago
BA
Data Engineer - Big Data & BI
BYD Australia & New Zealand
Mulgrave, NS
- Contract
Added 2 months ago
A
Agentic AI / Data Engineer - DC GPU
AMD
Oro-Medonte, ON
- $156,000 to $234,000 CAD / year
- Full-time
Added 2 months ago
FE
Data Engineer
Future Electronics
Kirkland, QC
- Full-time
This role is responsible for designing, building, and optimizing enterprise data pipelines that collect, transform, store, and prepare data for reporting, analytics, machine learning, and…
Added 3 months ago
T(
Staff Data Engineer
Tilt (f.k.a. Delphia)
Remote, Canada
- $210,000 to $270,000 CAD / year
- Full-time
- Remote
Added 2 months ago
ME
Data Engineer
MACLEAN ENGINEERING & MARKETING CO. LIMITED
Barrie, ON · Collingwood, ON · North Bay, ON · Sudbury, ON
- $70,000 to $120,000 CAD / year
- Full-time
Added 2 months ago
JG
DataOps/Cloud Data Engineer
J&M Group
Toronto, ON
- Full-time
Experience with Cloud data engineer must be familiar and experienced with different programming languages (Python, SQL, t-SQL, PL/SQL, Informatica, ADF, SSIS. Microsoft Fabric) and be able…
Added 5 months ago
PS
Senior Data Engineer
Pacific Smoke International Inc
Markham, ON
- $80,000 to $120,000 CAD / year
- Full-time
…who build, design, and support it. We’re looking for a Senior Data Engineer to join our scaling…
Added 2 months ago
BS
Sr. Data Engineer - AI & Data Science
B3 Systems
Toronto, ON
- Full-time
…leverage AI to dramatically enhance performance. As the Senior Data Engineer on our AI & Data Science team, you'll own the team's analytical data layer: the schemas, views, and pipelines…
Added 2 months ago
AM
Agentic AI / Data Engineer - DC GPU
Advanced Micro Devices, Inc
ON · ONTARIO-HOME OFFICE, Ontario
- Full-time
Added 2 months ago
PH
Sr. Data Engineer
Propel Holdings
Toronto, ON
- Full-time
Added 2 months ago
ZI
Senior Data Engineer
ZenaTech Inc.
Toronto, ON
- $115,000 to $130,000 CAD / year
- Full-time
Added 4 months ago
K
Senior Consultant, Azure Data Engineer
KPMG
ON · Toronto, Ontario
- Full-time
Added 2 months ago
PI
MLOps & Data Engineer
Palitronica Inc.
Waterloo, ON
- $90,000 to $120,000 CAD / year
- Full-time
Palitronica is seeking an MLOps & Data Engineer to develop, maintain, and extend the Python framework and data foundation behind our production machine-learning systems. Models and…
Added 2 months ago
JG
Data Engineer
J&M Group
Toronto, ON
- Contract
6 8+ years in production data pipeline L1/L2 support.
Added 2 months ago
Sr. Data Engineer, WW Pricing Data and Insights
Amazon
Vancouver, BC
You will be joining WW Pricing Data & Analytics team which consists of several Data Engineers and Business Intelligence Engineers.
Added 2 months ago
SH
Data Engineer
Spectrum Health Care
Toronto, ON
- Full-time
Are you a Data Engineer with experience building cloud-based data solutions and transforming healthcare data into actionable insights? At Spectrum Health Care (Spectrum), we're building a…
Added 2 months ago
A
Ingénieur de données Databricks / Data Engineer Databricks
Avanquest
Montreal, QC
- Full-time
Added 2 months ago
FL
Data Engineer (Databricks)
Fluent, LLC
Remote, Canada
- Full-time
- Remote
As a Data Engineer on Fluent's Data Engineering team, you will bring your Databricks development expertise to build the data products that power Fluent's Audience Solutions business: the…

Tilt (f.k.a. Delphia)

Staff Data Engineer

Remote, Canada

Remote

$210,000 to $270,000 CAD / year · Full-time

Apply About employer

Applications open in a new tab.

Job details

Pay: $210,000 to $270,000 CAD / year
Job type: Full-time
Workplace: Remote
Posting language: English
Posted: Jul 27, 2026

Original job description

About Agora Intelligence (d.b.a. Tilt)

Agora Intelligence is building the audited methodology layer agents call before touching portfolios. Our product, Tilt, is GitHub for rules-based investment methodologies: an open platform and marketplace where investment strategies are created, tested, audited, and distributed - by humans and AI agents alike. As AI agents begin managing real portfolios, they need a trusted source of verified investment logic before they can act. Tilt is that source.

We operate across two connected surfaces: InvestOS, an open standard that lets any brokerage or platform plug verified methodology into its own AI experience; and Tilt, the reference implementation of InvestOS. Tilt is an agentic harness where investors, portfolio managers, and creators can author, remix, and publish strategies. We're a small, senior team (from BlackRock, Bloomberg, BGI, and Quant Funds) backed by Portage Ventures, Lerer Hippeau, Cumberland Investments (and more), working with major brokerages and financial data providers.

What We're Building

InvestOS - an open standard for rules-based methodologies and its reference implementation.

We believe any idea - a theme, a trend, a thesis - can be turned into an investable view. On Tilt, anyone can express a view as a rules-based basket of assets in seconds, backed by evidence and scored against what actually happens. Whether you're modeling a thematic strategy, tracking an emerging technology, or capturing the public-market footprint of a private company, what used to take an index committee months now takes an API call - 100× faster, at a fraction of the cost. We also transform views found on the open web into rules-based strategies. This lets us measure the performance of any opinion or prediction about the future. The unit is a tilt: a creator-authored view of the world.

The bigger bet: as AI agents take on more of investing, they'll need an open, trusted standard for how investment views are expressed, verified, and combined. When anyone can generate a strategy in seconds, the strategies aren't the asset. The system that versions, tests, and grades them is. We're building that standard - and the platform where those views are made. We’re also building the learning loops for when views resolve against reality, as measured by markets.

Who We Are

We're a team of ~25 senior-to-principal engineers, designers and AI/ML researchers. More than half the team are former founders. We move fast, challenge assumptions, and believe AI should fundamentally change how financial products are built. We have no management hierarchy and work remotely with 4 one-week hackathons per year. “Full stack” to us means you own a slice of the product, including its roadmap and go-to-market.

The Opportunity

Creating an investable index from a conversation with AI isn't a traditional data engineering problem. Every investment methodology we generate depends on high-quality, continuously evolving data flowing reliably across hundreds of sources, pipelines, and systems.

We're looking for a Staff Data Engineer who thrives in ambiguity, enjoys building large-scale data platforms, and wants to define how AI-native investing is powered behind the scenes.

You'll work directly with the founders, product engineers, and AI/ML researchers to build the data foundation that powers everything we do. This isn't a role where you'll simply maintain pipelines. You'll help identify opportunities, influence our data strategy, and set the standard for data engineering across Tilt.

What You'll Do

Design and build the data platform that powers methodology generation, AI reasoning, analytics, and investment products.
Develop reliable, scalable pipelines that ingest, transform, and enrich structured and unstructured financial information.
Build systems that continuously process data from filings, market data, news, research, and other external sources.
Design data models that support product development, machine learning, and long-term platform evolution.
Ensure our data is accurate, observable, reliable, and available when every downstream system depends on it.
Make thoughtful tradeoffs between data quality, performance, scalability, and operational simplicity.
Raise the quality of data engineering across the company through technical leadership, architecture, and best practices.
Continuously improve how we build by leveraging AI throughout development, testing, monitoring, and data quality workflows.

Who You Are

You've spent years building production data platforms, not just ETL pipelines, and understand the difference.
You naturally think about how data enables products, not just how it's stored.
You have strong engineering fundamentals and are comfortable designing distributed data systems at scale.
You're able to simplify complex data architectures into systems that are reliable, maintainable, and easy to extend.
You understand that trustworthy AI starts with trustworthy data.
You communicate technical ideas clearly and enjoy working closely with engineers, AI researchers, and founders.
You're comfortable taking ownership without waiting for direction and enjoy solving foundational infrastructure problems.
You believe AI should fundamentally change how financial data is collected, processed, and used.

What Sets You Apart

Experience building large-scale data platforms, streaming pipelines, or modern data infrastructure.
Experience working with financial, market, or other high-volume information sources.
Strong experience with distributed systems, cloud infrastructure, and data orchestration.
Experience supporting machine learning or AI platforms with high-quality data pipelines.
Experience at an early-stage startup where you've owned significant platform or infrastructure decisions.
You're energized by building systems that quietly power everything else.

What We Offer

Competitive base salary and meaningful equity package
Direct partnership with the founders and a team where more than half are former founders.
Comprehensive health and dental benefits.
A remote-first, flexible work environment.
The opportunity to help define a company creating a new category in capital markets.

How to Apply

Apply through Bookface and include:

A link to your GitHub, portfolio, or examples of your work.
A short note about a data platform or infrastructure project you've built that you're most proud of, including the problem you solved and your role in the outcome.
A few sentences on why you're interested in Tilt.

Apply About employer

More about this job

Responsibilities

Design and build a scalable data platform to power AI-driven investment methodology generation and analytics. Develop reliable pipelines to ingest and enrich structured and unstructured financial data from diverse external sources.

Requirements

Requires extensive experience building production-grade distributed data platforms and infrastructure, specifically within high-volume or financial contexts. Candidates must demonstrate strong engineering fundamentals and the ability to lead technical strategy in an early-stage startup environment.

Skills

Data Platform Design
Distributed Systems
Data Pipeline Engineering
Financial Data Modeling
Cloud Infrastructure
Data Orchestration
ETL
Streaming Pipelines
Machine Learning Infrastructure
Technical Leadership
System Architecture
Data Quality Assurance

Benefits

Competitive base salary
Meaningful equity package
Comprehensive health benefits
Dental benefits

Visa sponsorship

Not detected in the job text

Keywords

Data Engineering
AI
Machine Learning
Financial Data
InvestOS
Distributed Systems
Cloud Infrastructure
Data Pipelines
Streaming
Market Data
Data Modeling
Scalability
Observability
FinTech
Capital Markets
Infrastructure
API
Unstructured Data
Data Orchestration
Technical Architecture

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