Top Analytics Jobs in Vancouver

Design and maintain dbt data models and end-to-end pipelines, write complex SQL and macros, ensure data quality, build BI dashboards, and collaborate with analysts to maintain consistent metrics.

The role involves maintaining financial data models, optimizing data pipelines, executing financial reports, and providing strategic analysis leveraging SQL and BI tools.

The Senior Client Analytics Partner will help B2B clients optimize marketing strategies and measure success through advanced analytics, reporting, and client collaboration.

Design, build, and deploy scalable ML solutions using GCP and Vertex AI. Collaborate with teams to operationalize models and monitor performance.

As a Senior Engineer on the Data Platform team, you will design and build data pipelines and optimize storage systems to enhance analytics and machine learning capabilities.

The Senior Analytics Developer leads the development of data pipelines, transformations, and models in a data lake, collaborating with stakeholders to create data solutions and ensuring data accuracy.

The Analytics Engineer will support data analysis and optimization of conversational AI systems, automate processes, and maintain data pipelines and dashboards.

The Senior Analytics Engineer will develop scalable analytics solutions, optimize SQL queries, and recommend data improvements while collaborating with various stakeholders.

The GenAI Engineer will design, build, and deploy Generative AI solutions, focusing on reinforcement learning and multi-agent workflows, while collaborating with various teams to enhance model performance.

Design and lead the development of cloud-native Generative AI platforms and solutions, ensuring scalability, security, and integration with enterprise applications.

The Analytics Manager will lead analytics for the Payments and Identity lifecycle, manage a team of analysts, develop KPIs, and ensure data quality while collaborating with cross-functional teams.

Lead the development of data-driven decision-making and analytics within the People & Culture function, automate key processes, and ensure data governance and security in a strategic leadership role.

Develop scalable micro-services in Go, work with large datasets across various databases, and utilize data lakehouse and real-time analytics technologies for efficient data processing.

Lead the data-driven culture at Arc'teryx by developing analytics strategies, automating processes, ensuring data governance, and mentoring a team.

The Product Manager - Analytics leads the strategy for analytics capabilities, collaborating with teams to create scalable solutions that improve mining operations.

Design, build, and maintain data models and end-to-end pipelines (dbt, SQL). Ensure data quality, optimize queries, and collaborate with analysts to deliver consistent product analytics and dashboards.

The Manager is responsible for leading the lifecycle of analytics products to enhance decision-making in Digital Commerce and Marketing, ensuring product delivery, stakeholder adoption, and establishing analytics standards.

The Manager of Analytics Products & Data Science leads the development of analytics products, ensuring they drive business impact through advanced analytics, collaboration, and effective measurement strategies while fostering team development and product adoption.

As an Analytics Engineer, you'll manage the data stack, design database architecture, build data pipelines, and oversee reporting and data quality.

As a Senior Analytics Engineer, you'll design scalable data models, define transformation standards, and translate business problems into data solutions while ensuring data governance and quality.

Lead a team of data analysts to improve product performance insights, establish experimentation practices, and enable self-service insights for the company.

Lead and mentor a team of analysts to elevate analytical quality, executing complex analyses and translating data into actionable business insights for pharma clients, while ensuring high standards in data hygiene and operational excellence.

As a Senior Agentic AI Engineer, you will lead innovation in AI initiatives, from ideation to prototyping, collaborating with teams to deliver impactful solutions.

Lead the Credit Risk & Analytics function, utilizing AI/ML for underwriting, portfolio monitoring, and collections strategy to enhance risk performance.

As a Machine Learning Engineer, you'll develop scalable ML solutions using Google Cloud Platform and Vertex AI, collaborate with teams, and operationalize models from ingestion to monitoring.