Nature & Scope 12 Your Role at Roots

As an Analytics Engineer, you19ll sit at the intersection of data engineering and analytics, turning raw retail data into trusted, scalable assets and the insights that bring them to life. As a collaborative member of our data team, you19ll contribute to the data models that power solutions across the Roots business and help build the data products, semantic layers, and self-service tools that empower every team at Roots to access trusted data independently. Our data team is small and collaborative, meaning you19ll wear multiple hats and have broad exposure across the business.

Key Responsibilities 12 How You19ll Make an Impact

• Support end-to-end data transformation, converting raw omnichannel source data (POS, e-commerce, inventory, CRM, and marketing) into clean, structured layers within Snowflake.
• Contribute to the design and build of components of the Snowflake data mart, applying dimensional modelling best practices including star schemas and slowly changing dimensions, to help create reliable, performant data products that serve ad hoc analysis, BI dashboards, and AI data solutions.
• Support Power BI report development end-to-end, from semantic model design to polished, publish-ready reports, giving commercial, merchandising, marketing, and finance teams self-service access to trusted data without analyst dependency.
• Perform ad hoc analysis using SQL and Python directly in Snowflake to help answer pressing business questions, uncover trends, and deliver timely insights that inform planning, buying, and operational decisions.
• Assist in maintaining data quality standards, including testing frameworks, pipeline alerting, and documentation, to help ensure the data mart is trustworthy and well-understood across the business.
• Support the development and maintenance of Gen AI data solutions, including natural language interfaces enabling any business user to query the data mart in plain English.
• Partner cross-functionally with merchandising, planning, marketing, and commercial teams to understand analytical needs and help translate them into scalable data products.
• Participate in the continuous improvement of our data platform, contributing ideas around new tools, patterns, and AI capabilities that keep Roots ahead of the curve.

Qualifications & Experience 12 The Skills You Bring

• 3+ years of experience in analytics engineering, data engineering, business intelligence, or an equivalent data analytics role.
• Strong SQL proficiency and hands-on experience with Snowflake or a comparable cloud data warehouse.
• Hands-on experience with ELT/ETL platforms, with Matillion or a similar cloud-native transformation tool preferred.
• Proficiency building data models and dashboards with Power BI.
• Solid understanding of dimensional modelling methodologies including star schemas and slowly changing dimensions.
• Experience with version control using Git.
• Familiarity with data quality practices including testing, documentation, and pipeline monitoring.
• Exposure to Gen AI solutions such as Snowflake Cortex or Microsoft Fabric Copilot is preferred.
• Retail or apparel industry experience across omnichannel environments is an asset.
• Python proficiency for data transformation, ad hoc analysis, or automation is a plus.

At Roots we appreciate that skills and expertise are cultivated through a range of experiences. We are committed to reflecting Canada19s diverse landscape in our products, team, and workplace culture. We value your unique perspective and encourage you to apply, even if you don19t meet every listed requirement. Accommodations are available for applicants throughout the recruitment process.

Please note: Roots uses technology-assisted tools, including artificial intelligence (AI), to support parts of the recruitment process. These tools may be used to help review applications, assess qualifications, and support interview documentation. All hiring decisions are reviewed and made by our Talent team and key leaders involved in the recruitment process.

The posted salary range is intended to reflect the competitive market value of this role and is provided to support transparency in our hiring process. Final compensation will be determined based on a variety of factors, including but not limited to internal equity, relevant skills, demonstrated knowledge, experience, and overall fit for the position.