Senior Data Analyst (SQL, Power BI, Looker)
100% remote work flexibility within CanadaFull-TimeSenior
Salary62 - 65 CAD per hour
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Job Details
- Experience
- 5+ years of experience in data analysis, business intelligence, or a related quantitative role.
- Required Skills
- AWSPythonSQLMicrosoft Power BISnowflakeProduct AnalyticsAirflowAzureData modelingSaaSdbtLookerR
Requirements
- 5+ years of experience in data analysis, business intelligence, or a related quantitative role.
- Strong proficiency in SQL for querying, transforming, and analyzing large datasets.
- Hands-on experience with Power BI and Looker or similar data visualization tools.
- Solid experience with data warehousing and ELT tools such as Snowflake, Airflow, or dbt.
- Proficiency in Python or R for data analysis, modeling, and statistical work.
- Strong understanding of statistical analysis, data modeling, and analytical methodologies.
- Experience working with cloud platforms such as AWS or Azure.
- Ability to translate complex data into clear, actionable business insights.
- Strong communication skills and ability to present findings to diverse stakeholders.
- Bachelor’s degree in Data Science, Statistics, Mathematics, or a related field (Master’s is an asset).
- Experience in SaaS, product analytics, or large-scale digital platforms is an advantage.
Responsibilities
- Partner with product managers, engineers, and cross-functional stakeholders to identify business challenges and deliver data-driven solutions supporting product and strategic goals.
- Analyze large, complex datasets to extract insights that inform product strategy, user behavior understanding, and business performance optimization.
- Build and maintain dashboards and visual reports using tools such as Power BI and Looker to track KPIs and OKRs across platform initiatives.
- Develop and refine data models and apply statistical techniques to forecast trends and support decision-making.
- Ensure data accuracy and integrity through validation, cleaning, and transformation best practices while resolving inconsistencies in datasets.
- Proactively identify trends, patterns, and opportunities that improve platform performance and business outcomes.
- Communicate analytical findings clearly to both technical and non-technical stakeholders to support informed decision-making.
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