Closed listing
Senior Business Intelligence Engineer
- Toronto, ON, Canada
Full-time
This opening has closed.
The original listing is kept below for reference.
Job details
- Job type
- Full-time
- Closing date
- Experience
- 5+ years of experience in Business Intelligence, Analytics Engineering, Data Engineering, or related disciplines.
- Posting language
- English
- Posted
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Search current openingsOriginal job description
Archived listing. The details below describe a past opening.
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*
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.
- 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.
- 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.
- 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.
- 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.
- 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.
- 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.
Data & Analytics
- Advanced SQL Development
- Dimensional Data Modeling
- Semantic Layer Design
- Data Warehousing
- Enterprise Reporting Architecture
- Google Cloud Platform (GCP)
- BigQuery
- Data Pipelines
- Git / Source Control
- Data Integration & Transformation
- Strategy (MicroStrategy) or similar enterprise BI platforms
- Semantic Models
- Self-Service Analytics
- Report Performance Optimization
- KPI & Metrics Governance
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
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
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Categories
- Data & Analytics
- Technology
- Software
- Finance & Accounting
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