Jobs in Ontario

Jobs across Ontario, Canada. Choose a city or town to search nearby.

201,027 listings · 20,873 employers Counted Nov 4, 2026. How we count

About these jobs

Employers hiring include Loblaw Companies Limited (5,131 listings), Shoppers Drug Mart (3,963 listings), Walmart Canada (3,305 listings).

Common roles: Retail sales associate, Practical nurse, Registered nurse.

32,899 of these listings include employer-provided pay. Open a job to see its currency and pay period.

Advertised starting pay
Pay period	Median starting pay	Listings
CAD / hour	23.00	16,959
CAD / year	80,000.00	13,205
USD / year	100,000.00	808
USD / hour	20.00	682
CAD / month	4,638.66	59
CAD / week	1,500.00	40
CAD / day	101.00	23

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.

Workplace classifications: 0% remote, 17% hybrid, 82% on-site, 0% not specified. Hybrid and on-site classifications may be inferred from descriptions. Check the original ad.

Based on the dated count above. Listings can change. How we count

Jobs in Ontario

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IT Accel, Inc.

Sr. AI Data Platform Engineer (FinOps Reporting)

Toronto, ON, Canada

Full-time

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Applications open in a new tab.

Job details

Job type: Full-time
Experience: 10 years of experience in data engineering, analytics engineering, BI engineering, financial data analytics, or a related data-focused role.
Posting language: English
Posted: Nov 4, 2026

Original job description

Hybrid 4 days onsite, 1 remote.

Position Summary

Our client is seeking a data professional with strong experience in data engineering, analytics engineering, BI engineering, financial data analytics, or a related data-focused role. The position focuses on building and maintaining FinOps data pipelines, integrating technology and financial data across enterprise systems, and developing trusted datasets and analytics to support cost management, reporting, forecasting, optimization, and auditability.

Responsibilities

Build and maintain FinOps data pipelines from ingestion through reporting and self-service analytics.
Normalize cloud and technology spend data across provider feeds, including alignment with standards such as FOCUS where applicable.
Integrate billing, usage, tagging, metadata, CMDB, application, owner, finance, contract, and vendor data.
Support cost taxonomy, allocation rules, metadata standards, showback, chargeback, forecasting, and auditability.
Create trusted datasets for cost reporting by business unit, product, application, environment, owner, platform, and vendor.
Build analytics to support budget guardrails, variance reporting, anomaly detection, remediation workflows, and optimization tracking.
Support commitment-based spend analysis, including reservation, savings plan, coverage, utilization, and waste reporting.
Develop reporting for rightsizing, idle resource cleanup, quota tuning, license reclamation, and other optimization opportunities.
Build models and dashboards for unit economics, total cost of ownership (TCO), ROI tracking, and business outcome-based cost analysis.
Partner with Engineering Analytics to deliver enterprise dashboards, automated alerts, recommendations, and workflow automation.
Ensure data quality, lineage, reconciliation, documentation, controls, and auditability across FinOps data assets.
Reduce manual reporting and spreadsheet dependency through automation.
Qualifications
10 years of experience in data engineering, analytics engineering, BI engineering, financial data analytics, or a related data-focused role.
University degree in Computer Science, Data Engineering, Information Systems, Engineering, Mathematics, Finance, Business Analytics, or a related field.
Strong experience with SQL, data modeling, ETL/ELT pipelines, and large, complex datasets.
Experience integrating data across multiple enterprise systems.
Experience with data platforms such as Databricks, Snowflake, BigQuery, Azure Synapse, Microsoft Fabric, SQL Server, or similar tools.
Experience with BI and reporting tools such as Power BI, Tableau, Looker, or similar platforms.
Strong understanding of data quality, reconciliation, controls, lineage, documentation, and governance.

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More about this job

Responsibilities

Build and maintain FinOps data pipelines and trusted datasets by integrating cloud spend, usage, financial, and enterprise system data. Develop reporting and analytics for cost allocation, forecasting, optimization, unit economics, and auditability while automating workflows and reducing manual reporting.

Requirements

Requires 10 years of experience in data engineering, analytics engineering, BI engineering, financial data analytics, or a related field, plus a university degree in a relevant discipline. Candidates should have strong SQL, data modeling, ETL/ELT, enterprise data integration, data platform, BI reporting, and data governance experience.

Skills

Data Engineering
Analytics Engineering
BI Engineering
SQL
Data Modeling
ETL/ELT Pipelines
FinOps Data Pipelines
Financial Data Analytics
Data Integration
Data Quality
Data Governance
Cloud Cost Management
Cost Forecasting
Business Intelligence
Data Reconciliation
Data Lineage

Visa sponsorship

Not detected in the job text

Keywords

FinOps
SQL
Data Modeling
ETL/ELT
Data Pipelines
Databricks
Snowflake
BigQuery
Azure Synapse
Microsoft Fabric
SQL Server
Power BI
Tableau
Looker
FOCUS
Cloud Spend
Cost Allocation
Showback
Chargeback
Cost Forecasting
Anomaly Detection
Commitment-Based Spend Analysis
Reservations
Savings Plans
Rightsizing
Unit Economics
Total Cost of Ownership
ROI Tracking
Data Quality
Data Lineage

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