About the role

Data Analyst at Tucows analyzing data to generate insights for the Finance team. Collaborating across teams for analytics and reporting.

Responsibilities

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.
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.
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.
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.
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.

3+ years in a Data Analyst, Analytics Engineer, or BI Analyst role in a modern cloud data stack environment.
Advanced SQL including CTEs, window functions, joins, and performance-aware querying in Snowflake or a comparable cloud warehouse.
Hands-on experience with Looker: dashboard development, Explores, LookML, governed metrics, and enabling self-service analytics for business users.
Ability to read, maintain, test, and document dbt models. Familiarity with sources, tests, macros, lineage, and dbt development workflows.
Solid understanding of GL, journal entries, trial balance, financial statements, reconciliations, and period-close processes. SOX/ITAC experience is highly valued.
Working knowledge of dimensional modeling — fact/dimension tables, star schemas, slowly changing dimensions.
Applied experience with regression, classification, A/B testing, segmentation, and forecasting using SQL, Python, or similar tools.
Ability to explain complex analysis clearly to both Finance leadership and technical peers. Strong written and verbal skills.
Comfortable with Git/GitHub: branching, PRs, and collaborative development in a terminal environment.
Experience with LLMs or AI-assisted analytics tools (Claude, Gemini, GPT, Looker Conversational Analytics). Exposure to Cortex Analyst, Cortex Search, or AISQL capabilities. Understanding of MCP integration patterns is a plus.