Data Analyst

Rakuten Kobo Inc.•Toronto, ON

8d•$97,020 - $147,020•Hybrid

About The Position

Rakuten Kobo Inc. is seeking an experienced Data Analyst to join our Data Storytelling & Insights team, working closely with our engineering foundations. This role blends strong technical ownership of analytics‑ready data with the ability to translate complex information into clear, actionable insights. You’ll work end‑to‑end across the analytics lifecycle—building scalable, trusted data models and partnering with stakeholders to deliver dashboards and analyses that inform key business decisions.

Requirements

Bachelor’s degree in Computer Science, Data Science, or related field.
5+ years of experience in data analytics, analytics engineering, or BI, with demonstrated ownership of analytics data pipelines and models.
Strong SQL skills, including complex joins, window functions, and working with semi‑structured or nested data.
Solid understanding of data modeling and designing tables for downstream analytics and reporting use cases.
Strong analytical thinking, problem‑solving, and communication skills.
Experience working with modern cloud data warehouses (BigQuery preferred).
Hands‑on experience with Dataform (experience with dbt is a plus).
Experience with BI and visualization tools such as Tableau, Looker, or Domo.
Familiarity with analytics engineering best practices (e.g., testing, CI/CD for data).

Nice To Haves

Experience using LLM‑based coding assistants to support analytics or data engineering workflows.
Working knowledge of Python for analysis, automation, or ML‑adjacent use cases.
Familiarity with cloud platforms (Google Cloud Platform preferred).
Experience with Git‑based version control and analytics workflow automation.

Responsibilities

Design, build, and maintain analytics‑ready data models and pipelines using Dataform and BigQuery, including migrating and modernizing legacy logic into clearer, more reusable, and better governed data assets.
Ensure analytics code and pipelines are reliable, well‑documented, and suited for downstream reporting, experimentation, and analysis.
Build and maintain Tableau dashboards and reports that are reusable, trustworthy, and grounded in centralized, well‑modeled data.
Translate ambiguous business questions into clear analyses that explain what happened, why it happened, and what to do next.
Partner with business stakeholders and analytics peers to define requirements, metrics, and scalable analytics solutions.
Contribute to shared analytics standards and best practices across SQL, Dataform, Tableau, and documentation.
Leverage modern AI tools and LLM‑based coding agents to accelerate analytics workflows (e.g., SQL development, modeling, debugging, documentation), while applying strong judgment to validate correctness, performance, and data quality.