Senior Data Analytics Engineer - Data Insights

**This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Data Analytics Engineer - Data Insights based in Canada .** This role offers the opportunity to shape a company-wide data ecosystem by building trusted analytics foundations from the ground up. You will transform complex data sources into reliable models, metrics, and insights that empower smarter business decisions. Working at the intersection of data engineering, analytics, and business strategy, you will help define how teams understand and use information. You will collaborate with cross-functional stakeholders to create scalable data solutions, improve self-service analytics, and strengthen data-driven decision-making. The position is ideal for an experienced analytics engineer who enjoys solving complex problems, building impactful data assets, and improving data quality at scale. You will join a remote-first environment where ownership, collaboration, and continuous innovation are highly valued. ### Accountabilities: As a **Senior Data Analytics Engineer - Data Insights**, you will play a key role in designing and developing the company’s analytics foundation. You will build scalable data models, establish trusted metrics, and enable teams across the organization to make informed decisions through accessible and reliable data. - Partner with Analytics Engineers, Data Engineers, Data Analysts, and business stakeholders to understand decision-making needs and translate them into scalable data solutions. - Architect, build, test, and maintain reliable data models and pipelines using modern analytics engineering practices. - Develop and optimize data transformations within Snowflake and dbt environments to create trusted analytical datasets. - Design and implement metrics layers, dimensions, and KPI frameworks that support self-service analytics and consistent business reporting. - Establish best practices for data modeling, metric definitions, documentation, and analytics workflows. - Transform raw warehouse data into meaningful data assets that support dashboards, reporting, experimentation, and strategic analysis. - Improve data quality, reliability, and accessibility across the organization by developing scalable solutions. - Collaborate with technical and non-technical teams to ensure data products align with business priorities. - Manage complex analytics projects from concept through implementation while maintaining strong stakeholder communication. - Leverage AI tools and techniques to enhance development workflows, documentation quality, and analytics engineering efficiency. - Stay current with emerging technologies and industry trends to continuously improve data capabilities. ## Requirements: The ideal candidate is an experienced analytics engineering professional with strong technical expertise, a passion for high-quality data, and the ability to collaborate effectively in a distributed environment. - 5+ years of relevant industry experience in analytics engineering, data engineering, business intelligence, or related fields. - Expert-level SQL skills, including experience with advanced data modeling, query optimization, and analytical transformations. - Strong experience with data warehousing concepts, architecture, and best practices. - 3+ years of experience working with Python and dbt for data transformation and analytics development. - Hands-on experience building semantic layers, metrics layers, and self-service analytics solutions. - Proven ability to design and deliver scalable data solutions that support business growth. - Experience managing complex data projects independently from planning through delivery. - Strong analytical, problem-solving, and troubleshooting abilities. - Excellent communication skills, with the ability to explain technical concepts clearly to non-technical stakeholders. - Experience working effectively in remote, collaborative environments.…