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Arobas Personnel

Business Intelligence Engineer

  • Toronto, ON, Canada

Full-time

This opening has closed.

The original listing is kept below for reference.

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Job details

Job type
Full-time
Closing date
Experience
3+ years of experience in Business Intelligence, Analytics Engineering, Data Engineering, or a similar role.
Posting language
English
Posted

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Original job description

Archived listing. The details below describe a past opening.

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

This role is ideal for a data-driven professional who enjoys bridging business needs and technical solutions, while building scalable analytics and reporting environments in the cloud.

  • Remote : Hybrid*

Key Responsibilities

Semantic Layer Design & Data Modeling

  • Support the design, development, and maintenance of a centralized semantic layer within Google BigQuery, establishing a trusted source of business data.
  • Translate and consolidate business rules from legacy reports into standardized database logic to ensure consistent KPI definitions and reporting across departments.
  • Document business metrics, KPIs, dimensions, hierarchies, and calculation methodologies.
  • Develop reusable data models that support both operational and executive reporting requirements.

Data Engineering Collaboration

  • Partner with Data Engineering teams to ensure data quality, lineage, governance, and performance standards.
  • Support the integration and transformation of data from multiple business systems while maintaining clear end-to-end data lineage documentation.
  • Contribute to the design, documentation, and maintenance of SQL transformations, data models, and business logic supporting enterprise analytics.
  • Implement automated validation and reconciliation processes to improve data reliability.

Business Intelligence & Self-Service Analytics

  • Build and maintain semantic models that support enterprise BI and reporting platforms.
  • Collaborate with BI Developers to enhance reporting usability and performance.
  • Enable self-service analytics through governed datasets and reusable business metrics.
  • Support data security standards, including role-based and row-level access controls.

Business Analysis & Stakeholder Engagement

  • Gather and translate business requirements into functional and technical specifications.
  • Work closely with stakeholders across Finance, Sales, Revenue Operations, Product Management, and other business functions to understand reporting needs.
  • Facilitate discussions regarding KPI definitions, business rules, and reporting standards.
  • Document business processes, data definitions, and technical requirements.
  • Maintain business glossaries, metadata definitions, and documentation supporting data governance initiatives.

Required Qualifications

  • Bachelor's degree in Computer Science, Information Systems, Data Analytics, Engineering, or a related discipline.
  • 3+ years of experience in Business Intelligence, Analytics Engineering, Data Engineering, or a similar role.
  • Advanced SQL skills, including complex joins, aggregations, and performance optimization.
  • Experience working within large-scale enterprise data environments.
  • Strong expertise in dimensional modeling and analytics-focused data architectures.
  • Solid understanding of semantic layer concepts, data marts, and enterprise reporting frameworks.
  • Knowledge of ETL/ELT processes and data integration methodologies.
  • Experience with cloud analytics platforms, preferably Google Cloud Platform (GCP).
  • Experience with enterprise BI tools such as Strategy (formerly MicroStrategy) or comparable reporting platforms.
  • Strong analytical, problem-solving, and communication skills.

Preferred Qualifications

  • Hands-on experience with BigQuery, dbt, Dataflow, Airflow, or related cloud data technologies.
  • Experience designing and maintaining enterprise semantic layers and governed analytics environments.
  • Background in media, advertising, digital revenue, or high-volume transactional reporting environments is considered an asset.
  • Experience supporting financial reporting and reconciliation processes.
  • Knowledge of data governance, metadata management, and master data management (MDM) principles.

Technical Skills

Data & Analytics

  • Advanced SQL
  • Dimensional Data Modeling
  • Fact & Dimension Tables
  • Star Schema Design
  • Semantic Layer Architecture
  • Data Warehousing
  • ETL / ELT Processes

Cloud & Engineering

  • Google Cloud Platform (GCP)
  • BigQuery
  • Data Pipelines
  • Data Integration & Transformation

BI & Reporting

  • Strategy (MicroStrategy) or equivalent BI platforms
  • Semantic Models
  • Enterprise Reporting Solutions

Id

10032

Emplacement

Toronto

Durée De L'emploi

Temps Plein

Nombre D'emplois Vacants

1

Date Limite De Dépôt

Dernière mise à jour:

26-10-06 15:13
About employer
More about this job

Responsibilities

Design and maintain a centralized semantic layer, reusable data models, and standardized business metrics to support enterprise reporting and self-service analytics. Partner with data engineering teams and business stakeholders to improve data quality, governance, lineage, security, and reporting requirements.

Requirements

Requires a bachelor’s degree in a relevant discipline and at least three years of experience in business intelligence, analytics engineering, data engineering, or a similar role. Candidates should have advanced SQL, dimensional modeling, semantic layer and data warehousing expertise, knowledge of ETL/ELT and cloud analytics, and experience with enterprise BI platforms.

Skills

  • Advanced SQL
  • Dimensional Data Modeling
  • Semantic Layer Design
  • BigQuery
  • Google Cloud Platform
  • ETL/ELT
  • Data Integration
  • Data Warehousing
  • Data Pipelines
  • Strategy (MicroStrategy)
  • Enterprise Reporting
  • Data Governance
  • Metadata Management
  • KPI Definition
  • Data Quality
  • Stakeholder Engagement

Visa sponsorship

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Categories

  • Data & Analytics
  • Technology
  • Software
  • Finance & Accounting

Keywords

  • Business Intelligence
  • Analytics Engineering
  • Data Engineering
  • Advanced SQL
  • Google Cloud Platform
  • BigQuery
  • dbt
  • Dataflow
  • Airflow
  • Dimensional Modeling
  • Fact And Dimension Tables
  • Star Schema
  • Semantic Layer
  • Data Warehousing
  • ETL/ELT
  • Data Pipelines
  • Data Integration
  • Data Transformation
  • Strategy (MicroStrategy)
  • Enterprise Reporting
  • Self-Service Analytics
  • Data Governance
  • Metadata Management
  • Master Data Management
  • Data Lineage
  • Data Quality
  • Role-Based Access Control
  • Row-Level Security
  • Financial Reporting
  • Reconciliation

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