27 Analytics Engineer jobs in Canada available for remote work from home. Apply for positions such as Analytics Engineer, Analytics Engineer, Analytics Engineer II and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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The Analytics Engineer will lead the creation of enterprise data assets from scratch, transforming raw data into reliable sources of truth for strategic decision-making. They will collaborate with stakeholders to define data requirements, build scalable pipelines, and ensure effective monitoring and maintenance of data sets.
You will build and scale data pipelines and reporting infrastructure to support decision-making across the company. You will also collaborate cross-functionally to design scalable data models and maintain pipeline health.
You will independently design and maintain high-quality dimensional data models and ETL pipelines to support marketing analytics. Additionally, you will partner with cross-functional teams to translate business needs into trusted datasets while ensuring data quality and pipeline performance.
You will design and maintain enterprise marketing data models and semantic layers while acting as a strategic bridge between business stakeholders and technical execution. Additionally, you will architect data ecosystems to support autonomous AI agents and ensure robust data governance across cloud platforms.
The role involves designing and maintaining robust data systems, semantic layers, and dashboards to enable self-service analytics. The candidate will collaborate with stakeholders to translate business needs into actionable insights and mentor junior analysts.
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The role involves leading end-to-end analytics initiatives, setting standards for data models and pipelines, and partnering with Data Science and Product teams to solve complex monetization problems. You will also be responsible for architecting production-grade SQL pipelines and enabling self-serve analytics through high-quality dashboards.
You will own the data layer and design the analytics architecture, including a tiered platform for system of record, low-latency serving, and batch/ML processing. You will also be responsible for database performance, schema modeling, and implementing observability to ensure system reliability.
The Senior Analytics Engineer will build and scale the analytical foundation by transforming raw data into clean, trustworthy datasets for cross-functional teams. They will also design AI-ready data infrastructure and maintain semantic layers to support autonomous decision-making and AI-powered initiatives.
You will build and operate the core BI platform, owning data ingestion, integration, and architecture to support reporting and AI initiatives. Additionally, you will establish data governance standards, mentor analytics engineers, and ensure the reliability of data models and pipelines.
You will develop, maintain, and optimize data models while ensuring the reliability of data pipelines. Additionally, you will translate stakeholder requirements into efficient SQL queries and build internal dashboards to support operational teams.
The role involves evolving foundational data infrastructure to support the finance department, managing the end-to-end analytics pipeline from ingestion to reporting. You will collaborate with business and engineering teams to design schemas and promote software engineering best practices across the organization.
Design and maintain business-critical data systems and ETL pipelines to provide real-time visibility across various company departments. Analyze data to create business insights and build machine learning models to identify customer churn and upsell opportunities.
Guide the design and implementation of a unified data collection platform using Golang, Kubernetes, and ClickHouse to track product usage. Mentor other engineers and collaborate across teams to improve data quality and instrumentation reliability.
Develop end-to-end data pipelines and ingestion interfaces to provide analytical insights for strategic business domains. Collaborate with consultants and stakeholders to design and implement scalable data solutions and maintain data ecosystem health.
Design and maintain enterprise semantic models and data products to enable AI-powered decision-making and self-service BI. Partner with business stakeholders to translate domain knowledge into structured analytical representations and standardized KPIs.
Design, build, and maintain curated datasets and metric definitions to ensure reliable, consistent reporting across the organization. Partner with stakeholders to translate business requirements into data models while documenting logic for both human and AI-powered query tools.
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The Senior Analytics Engineer will build complex data infrastructure using dbt and Snowflake while implementing scalable ELT pipelines and governance frameworks. They will also provide technical guidance, conduct code reviews, and mentor junior team members to ensure high-quality data solutions.
Lead the design, development, and implementation of SAP-based data and analytics solutions including S/4HANA embedded analytics and SAC. Collaborate with cross-functional teams to translate functional requirements into technical data models and professional dashboards.
Lead the design, development, and implementation of SAP-based data and analytics solutions, focusing on SAC and S/4HANA. Create data models and professional dashboards to provide insightful data presentation for C-level executives and department heads.
The Advanced Analytics / AI Engineer will design and implement analytics solutions using MS Dynamics and Azure to support business objectives. They will also develop machine learning models and collaborate with cross-functional teams to derive actionable insights from complex datasets.
Define and drive the technical roadmap for Affirm's Lakehouse Platform, focusing on scalability, reliability, and cost-efficiency. Architect and implement secure data access capabilities and optimize performance across Snowflake and cloud-native storage.
Build and operate core platform capabilities for Affirm's data infrastructure, focusing on reliability, self-service automation, and data governance. Develop integrations and next-generation AI-native data tooling to support large-scale analytical use cases.
Design and build LLM-powered systems to transform how data practitioners interact with data through natural-language access and AI-assisted SQL. Develop end-to-end agentic workflows, retrieval systems, and quality evaluations to embed AI capabilities across the data infrastructure ecosystem.
Build highly scalable, distributed real-time micro-services using Go to power reporting, billing, and analytics. Transform foundational data into customer-facing insights through the development of pipelines and APIs.
You will lead the roadmap, architecture, and team responsible for the trusted data foundations that power 1Password’s business. This involves setting standards for data modeling, governance, and BI tooling while partnering with cross-functional leaders to support company-wide decision-making and AI initiatives.
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Lead and develop a team of analytics engineers to build a centralized, AI-ready data foundation and semantic layer. This hands-on role involves writing SQL/dbt code and partnering with cross-functional stakeholders to deliver scalable data products.
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