Senior Data Analyst
AI Summary
Senior Data Analyst on the Business Intelligence team at Sonatype, transforming complex product datasets into actionable insights, building scalable analytics infrastructure, mentoring associate analysts, and driving data-informed product decisions.
About this role
At Sonatype, we empower developers with best in class tools to build secure, high-quality software at scale. Our mission is to create a world where software is always secure and developers can innovate without fear. Trusted by thousands of organizations, including Fortune 500 companies, we are pioneers in software supply chain management, open source security, and DevSecOps.
We are looking for a Senior Data Analyst to join our Business Intelligence team. In this role, you will transform complex product datasets into actionable insights, build scalable analytics infrastructure, mentor associate-level analysts, and drive data-informed product decisions.
What You’ll Do:
Product Analytics & Telemetry: Analyze product usage, feature adoption, and telemetry data alongside financial metrics to optimize user experience and support product strategy.
Analytics & Data Modeling: Own the end-to-end analytics lifecycle, including data modeling, dashboard creation, and KPI development. Deliver high-accuracy analyses independently across various product initiatives.
Stakeholder Collaboration: Partner directly with cross-functional business stakeholders, managing requirements and delivering precise insights on tight turnarounds.
Mentorship: Serve as a technical guide to coach and mentor the team’s cohort of associate-level analysts.
Execution Metrics: Maintain high standards for ticket throughput, speed of delivery, and on-time completion rates for analytics tasks.
What You'll Bring:
Experience: 5+ years in data analysis, BI, or product analytics—specifically within a SaaS or tech company. Experience working with product telemetry/usage data is strictly required.
Location: Must be based in Canada (excluding Quebec; Ontario or Eastern time zone preferred).
Technical Stack:
Advanced SQL and Python skills.
Strong expertise in Databricks (PySpark, notebooks, data lakehouses/medallion architecture, AWS S3).
Hands-on experience with visualization tools—Looker is heavily preferred (or ability to quickly adapt from Power BI/Tableau).
Familiarity with APIs, structured data formats (JSON, DataFrames), and version control via GitHub.
Qualitative Traits: Strong curiosity, meticulous attention to detail, proactive problem-solving, and clear communication skills.
Nice to Have: Knowledge of business systems (Salesforce, HubSpot, Jira, Amplitude, Gainsight).
What we're proud of:
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