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Added 7 mins ago
NE
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Added 40 mins ago
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Added 40 mins ago
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Added 56 mins ago
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Arobas Personnel

Senior Business Intelligence Engineer

Toronto, ON, Canada

Full-time

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Job details

Job type: Full-time
Apply by: Nov 5, 2026
Experience: 5+ years of experience in Business Intelligence, Analytics Engineering, Data Engineering, or related disciplines.
Posting language: English
Posted: Oct 6, 2026

Original job description

Arobas Personnel is seeking a Senior Business Intelligence Engineer for a mandate with one of its clients located in Toronto.

This role is ideal for an experienced BI professional with strong expertise in data modeling, semantic layer architecture, cloud analytics, and enterprise reporting. You will play a key role in establishing governance standards, modernizing analytics capabilities, and delivering trusted business insights across the organization.

Remote : Hybrid*

Key Responsibilities

Semantic Layer Design & Data Modeling

Design, develop, and maintain a centralized semantic layer within Google BigQuery to serve as the organization's trusted source of business data.
Consolidate business rules from legacy reporting systems into standardized database logic, ensuring consistency in KPIs and reporting metrics.
Define and maintain business metrics, dimensions, hierarchies, and calculation methodologies.
Create scalable and reusable data structures that support operational, analytical, and executive reporting requirements.

Data Engineering Collaboration

Work closely with Data Engineering teams to ensure data quality, governance, lineage, and performance.
Develop and maintain complex SQL transformations and business logic.
Support data ingestion, integration, and end-to-end lineage mapping across multiple business domains.
Implement automated reconciliation, auditing, and validation processes.

Business Intelligence & Self-Service Analytics

Develop and maintain semantic models that power enterprise BI and reporting solutions.
Partner with BI Developers to optimize report performance, scalability, and user experience.
Enable self-service analytics through governed datasets and reusable business metrics.

Business Analysis & Stakeholder Engagement

Collaborate with stakeholders from Finance, Revenue Operations, Sales, Product Management, and other business units to understand reporting and analytics needs.
Lead discussions around KPI definitions, business rules, and reporting standards.
Provide governance and leadership for the definition, standardization, and ongoing maintenance of enterprise metrics and data definitions.

Data Governance & Quality

Provide oversight for business glossaries, data dictionaries, metadata repositories, and semantic layer documentation.
Promote best practices in data governance, data quality, and enterprise reporting standards.
Ensure consistency and accuracy of business definitions across analytics solutions.

Required Qualifications

Bachelor's degree in Computer Science, Information Systems, Data Analytics, Engineering, or a related field.
5+ years of experience in Business Intelligence, Analytics Engineering, Data Engineering, or related disciplines.
Advanced SQL expertise, including complex joins, aggregations, window functions, and query optimization.
Experience working in large enterprise data environments.
Strong expertise in dimensional data modeling and analytics architecture.
Experience designing and maintaining enterprise semantic layers, data marts, or reporting frameworks.
Deep understanding of ETL/ELT processes and data integration methodologies.
Experience with cloud analytics platforms, preferably Google Cloud Platform (GCP).
Hands-on experience with enterprise BI solutions such as Strategy (formerly MicroStrategy) or equivalent platforms.
Excellent analytical, problem-solving, stakeholder management, and communication skills.

Preferred Qualifications

Experience with BigQuery and modern cloud-based data platforms.
Proven experience implementing enterprise semantic layers and governed analytics solutions.
Experience in media, advertising, digital revenue, or similar high-volume reporting environments is considered an asset.
Experience supporting financial reporting and reconciliation activities.
Knowledge of data governance, metadata management, and master data management (MDM) principles.

Technical Skills

Data & Analytics

Advanced SQL Development
Dimensional Data Modeling
Semantic Layer Design
Data Warehousing
Enterprise Reporting Architecture

Cloud & Engineering

Google Cloud Platform (GCP)
BigQuery
Data Pipelines
Git / Source Control
Data Integration & Transformation

BI & Reporting

Strategy (MicroStrategy) or similar enterprise BI platforms
Semantic Models
Self-Service Analytics
Report Performance Optimization
KPI & Metrics Governance

Id

10033

Emplacement

Toronto

Durée De L'emploi

Temps Plein

Nombre D'emplois Vacants

1

Date Limite De Dépôt

Dernière mise à jour:

26-10-06 15:18

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More about this job

Responsibilities

Design and maintain a centralized semantic layer, standardized business metrics, and scalable data models in BigQuery to support enterprise reporting and self-service analytics. Collaborate with data engineering teams and business stakeholders to improve data quality, governance, lineage, reporting performance, and consistency of enterprise definitions.

Requirements

Requires a bachelor's degree in a relevant field and at least five years of experience in business intelligence, analytics engineering, data engineering, or a related discipline. Candidates should have advanced SQL, dimensional modeling, semantic layer and ETL/ELT expertise, experience with enterprise BI platforms and large data environments, and strong analytical and communication skills.

Skills

Advanced SQL
Dimensional Data Modeling
Semantic Layer Design
Data Warehousing
Enterprise Reporting
Google Cloud Platform
BigQuery
Data Pipelines
Data Integration
ETL/ELT
Strategy (MicroStrategy)
Self-Service Analytics
KPI Governance
Data Governance
Metadata Management
Stakeholder Management

Visa sponsorship

Not detected in the job text

Keywords

Business Intelligence
Analytics Engineering
Data Engineering
Advanced SQL
Google Cloud Platform
BigQuery
Semantic Layer
Dimensional Data Modeling
Data Warehousing
Enterprise Reporting
ETL/ELT
Data Integration
Data Pipelines
Strategy (MicroStrategy)
Semantic Models
Self-Service Analytics
KPI Governance
Data Governance
Data Quality
Data Lineage
Metadata Management
Master Data Management
Financial Reporting
Reconciliation
Git
Cloud Analytics
Business Metrics
Query Optimization
Data Dictionaries
Business Glossaries

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