Senior Data Analyst, Product Analytics

Autodesk•Vancouver, BC

3d•CA$107,000 - CA$156,200•Hybrid

About The Position

Data is central to how we understand customer behavior, measure product success, and build better experiences for our customers. Autodesk is seeking a Senior Data Analyst - Product Analytics to join the Product Development & Manufacturing Solutions organization. In this role, you'll partner closely with Product Managers, Engineering, Design, Finance, Sales, and Marketing to transform product data into actionable insights that influence product strategy and business outcomes. As a trusted analytics partner, you will help answer critical questions about feature adoption, customer engagement, retention, and product health. You'll define meaningful success metrics, develop scalable measurement frameworks, and uncover opportunities to improve the customer experience through data. We're looking for someone who thrives in ambiguity, is naturally curious, and enjoys asking difficult questions that lead to better decisions. You combine strong analytical thinking with business acumen and exceptional communication skills to translate complex analyses into compelling stories that drive action. At Autodesk, we value a hybrid work culture. Remote work is supported in Toronto and Vancouver, Canada. If you live near one of our offices, you're welcome to work there full- or part-time based on your preference.

Requirements

5+ years of experience in Product Analytics, Data Analytics, or Business Analytics, including experience influencing product or business decisions through data
Demonstrated experience presenting analytical findings and recommendations to senior leadership and executive audiences
Expertise in SQL and working with modern cloud data warehouse environments
Advanced experience building dashboards and visualizations using Power BI (required); experience with Tableau or Looker is a plus
Experience analyzing event-based product telemetry, clickstream, or user behavior datasets
Strong understanding of analytical methods, hypothesis-driven problem solving, and translating ambiguous business questions into measurable analyses
Experience working with modern analytics engineering and data pipeline technologies (DBT, Airflow, GitHub, or similar)
Bachelor's degree in a quantitative field (Computer Science, Statistics, Mathematics, Economics, Engineering, or equivalent practical experience)

Nice To Haves

Experience with experimentation frameworks, A/B testing, or product measurement methodologies
Experience using Python (pandas, Jupyter, NumPy, or similar) for exploratory analysis and automation
Familiarity with product analytics platforms such as Amplitude, Mixpanel, Pendo, or similar tools
Experience integrating product analytics with Sales and Marketing data sources (Salesforce, Marketo, etc.)
Experience working within SaaS or cloud software organizations

Responsibilities

Partner with Product Managers and Engineering teams throughout the product lifecycle to define success metrics and measurement strategies before features launch
Analyze product telemetry, clickstream, and user behavior data to identify opportunities that improve customer engagement, adoption, and retention
Design, maintain, and evolve scalable product KPIs and data models that provide consistent measurement across products
Build self-service dashboards, reports, and visualizations that enable teams to independently explore product performance while maintaining trusted business definitions
Conduct deep-dive analyses to understand product usage, customer journeys, and feature performance, translating findings into actionable recommendations
Develop hypotheses, evaluate product changes, and support experimentation and A/B testing where applicable
Partner with Data Engineering to improve event instrumentation, data quality, and analytics infrastructure
Communicate analytical findings to executive and cross-functional audiences through clear storytelling and data visualization
Improve analytics documentation, metric definitions, and best practices to promote consistency and scalability across teams