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Principal Data Analyst
Autodesk
Vancouver, CAN
Full-time
Mid-Senior
Onsite
CAD 99,000 to CAD 145,200.
Discovered 3 weeks ago
Product analyticsSQLPythonRAI-assisted development and analysisStatistical analysis and modeling
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Product analyticsSQLPython
Role Overview
Autodesk is seeking a Principal Data Analyst to serve as a senior individual contributor and trusted thought partner to product, engineering, strategy, research, and business leaders.
The role defines success measures, uncovers high-value opportunities, leads experimentation, and builds analytical products and AI-assisted workflows.
The position combines product analytics judgment, SQL and Python capability, software engineering discipline, and practical use of modern AI tools.
Key Skills for This Role
Product analyticsSQLPythonRAI-assisted development and analysisStatistical analysis and modeling
Full Job Posting
Position Overview
Autodesk is seeking a Principal Data Analyst to serve as a senior individual contributor and trusted thought partner to product, engineering, strategy, research, and business leaders.
The role defines success measures, uncovers high-value opportunities, leads experimentation, and builds analytical products and AI-assisted workflows.
The position combines product analytics judgment, SQL and Python capability, software engineering discipline, and practical use of modern AI tools.
Responsibilities
- Identify business problems and opportunities through data analysis and derive actionable insights from complex datasets.
- Define product measurement using north-star metrics, KPI/OKR frameworks, metric trees, instrumentation, guardrails, and launch measurement.
- Use AI tools to accelerate analysis, automate workflows, prototype data applications, and create reusable validated workflows.
- Create visualizations with Power BI, Looker, or similar tools.
- Build canonical datasets, semantic models, metric definitions, dashboards, and self-service analytics experiences.
- Support platform outcomes through insights on performance, user engagement, and business impact.
- Partner with Data Engineering on data quality, lineage, observability, and scalable pipelines.
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