Data Analyst
The majority of our roles are remote-first, meaning you can work from anywhere you can connect to the Internet! Today, over one thousand people work in over 20 countries to help us make the Internet better.Full-TimeMiddle
Salary79,650 - 88,500 CAD per year
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Job Details
- Experience
- 3+ years in a Data Analyst, Analytics Engineer, or BI Analyst role
- Required Skills
- PythonSQLGitSnowflakeData modelingA/B testingdbtLookerGitHub
Requirements
- Experience: 3+ years in a Data Analyst, Analytics Engineer, or BI Analyst role in a modern cloud data stack environment.
- SQL mastery: Advanced SQL including CTEs, window functions, joins, and performance-aware querying in Snowflake or a comparable cloud warehouse.
- Looker expertise: Hands-on experience with Looker: dashboard development, Explores, LookML, governed metrics, and enabling self-service analytics for business users.
- dbt proficiency: Ability to read, maintain, test, and document dbt models. Familiarity with sources, tests, macros, lineage, and dbt development workflows.
- Finance domain knowledge: Solid understanding of GL, journal entries, trial balance, financial statements, reconciliations, and period-close processes. SOX/ITAC experience is highly valued.
- Data modeling: Working knowledge of dimensional modeling — fact/dimension tables, star schemas, slowly changing dimensions.
- Statistical & predictive analysis: Applied experience with regression, classification, A/B testing, segmentation, and forecasting using SQL, Python, or similar tools.
- Communication: Ability to explain complex analysis clearly to both Finance leadership and technical peers. Strong written and verbal skills.
- Version control: Comfortable with Git/GitHub: branching, PRs, and collaborative development in a terminal environment.
Responsibilities
- SQL & Business Analysis: Translate ambiguous business questions into precise SQL queries against our Snowflake warehouse. Own and deliver recurring financial reporting, reconciliation, and operational analytics with an eye for improving efficiency over time.
- Diagnostic & Advanced Analytics: Go beyond dashboards to explain why metrics move. Conduct root cause analyses, build forecasting models, and support decision-making through churn analysis, customer segmentation, CLV, A/B testing, and similar techniques.
- Business Intelligence & Self-Service Analytics: Build, maintain, and optimize Looker dashboards, Explores, and LookML definitions that provide governed, reliable, self-service analytics. Govern the semantic layer — metrics, dimensions, and business logic — that powers trusted reporting and AI-enabled analytics. Train business users to leverage these tools confidently.
- Finance Partnership & Compliance: Serve as the primary analytical partner to the Finance team. Own financial reporting, reconciliation, and forecasting workflows. Support SOX audits and ITAC testing, ensuring financial data is accurate, auditable, and well-documented.
- Data Quality & Cross-Functional Collaboration: Monitor and improve data quality across analytical pipelines, especially for finance-critical datasets. Gather requirements from stakeholders, translate business needs into technical specs, and collaborate with Data and Analytics Engineers to resolve upstream issues.
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