Analytics Engineer

This position is posted by Jobgether on behalf of a partner company. We are currently looking for an Analytics Engineer in Canada.

In this role, you will help shape the future of data-driven decision-making within a large-scale consumer technology environment. Working at the intersection of Data Science and Data Engineering, you will design and maintain scalable analytics infrastructure that empowers teams to improve products, user engagement, and business performance. You will collaborate closely with cross-functional stakeholders including Product, Engineering, Design, and Data Science to develop reliable pipelines, reporting systems, and self-service analytics tools. This position offers the opportunity to work with massive datasets and modern technologies in a highly collaborative and innovative setting. Ideal candidates are passionate about transforming data into actionable insights, building scalable systems, and driving operational excellence through automation and analytics. The environment is fast-paced, impact-driven, and focused on continuous learning and technical growth.

• Lead analytics engineering initiatives focused on improving data quality, reliability, performance, and automation across consumer-focused products and services.
• Design, develop, and maintain scalable ETL and ELT pipelines to support reporting, experimentation, user analysis, and product performance tracking.
• Partner closely with Data Scientists, Product Managers, Engineers, and Designers to create robust data foundations and analytics solutions.
• Build and maintain dashboards, reporting systems, aggregations, and internal analytics tools that streamline data access and decision-making.
• Ensure the integrity and governance of structured and unstructured datasets across large-scale data environments.
• Drive the adoption of self-service analytics capabilities and contribute to building a strong data-driven culture.
• Collaborate with engineering teams to improve data collection architecture, workflow efficiency, and pipeline reliability.
• Provide mentorship, technical guidance, and support to data science and technical teams on analytics engineering best practices.
• Contribute to long-term data strategy discussions and help shape scalable analytics foundations for future growth.

Requirements:

• Bachelor’s degree in a quantitative field such as Computer Science, Statistics, Applied Mathematics, Economics, Physics, or a related discipline.
• Minimum 4 years of experience working with large-scale ETL systems and production-level data engineering or analytics engineering environments.
• Strong programming skills in Python, SQL, Spark, Scala, or related technologies.
• Hands-on experience with data modeling, data governance, workflow orchestration tools, and scalable data processing systems.
• Familiarity with platforms and tools related to front-end or back-end engineering, analytics tooling, and dashboard development.
• Strong understanding of relational and massively parallel processing (MPP) databases and technical data architecture principles.
• Experience working with massive-scale structured and unstructured datasets in cloud or distributed environments.
• Excellent communication and collaboration skills, with the ability to work effectively across technical and non-technical teams.
• Proven ability to work independently, prioritize effectively, and manage projects in a fast-paced environment.
• Experience within consumer product organizations and exposure to AI-assisted development workflows are considered strong assets.

Benefits:

• Flexible remote-first work environment with optional access to physical office locations.
• Comprehensive healthcare coverage including medical, mental health, and wellness support programs.
• Family planning and gender-affirming care benefits.
• Registered Retirement Savings Plan (RRSP) with company matching contributions.
• Flexible vacation policy and paid volunteer time off.
• Generous paid parental leave programs.
• Professional development and workspace support benefits tailored to individual needs.
• Income replacement and financial wellbeing programs.
• Inclusive and collaborative workplace culture committed to diversity, accessibility, and equal opportunity employment.