Data Product Analyst

Managing a data project from start to finish using agile method, helping stakeholders to refine their questions into structured data projects, advising stakeholders on what to measure, how to model it, and which tool to use and facilitating stakeholder discussions to bridge the gap between high-level business goals and technical execution. Deliver end-to-end solutions, from ingestion and modeling to executive-ready visualizations and summaries. You act as a bridge to Data Engineering. You’ll proactively surface data debt, documentation gaps, and tooling friction to ensure the platform gets simpler and stronger over time. You’ll also ensure high standards for PII handling and security policies are built into every delivery.

Sonar is driving the future of agent-centric software development. As the leader in AI code review and verification, we solve a critical problem: ensuring that software generated by AI-assisted developers or autonomous agents is reliable, secure, and maintainable. Our team operates across global hubs in Austin, Bochum, Dubai, Geneva, London, Singapore, Tokyo, and Washington D.C. With over $400M in revenue and profitable, fast-paced growth, we are building the backbone of the AI software revolution.

• 3–5+ years in a Data Analyst, Data Product Analyst, or Analytics Engineering role, ideally within a fast-paced environment.

• A track record of taking the lead with stakeholders—successfully translating high-level business ambiguity into structured, actionable data projects. You have experience helping and mentoring other team members.

• Hands-on experience with dbt / SQL (modeling, testing, and documentation).

• Hands-on experience with data visualization tools (Tableau, Mixpanel, or similar)

• Comfort working in a version-controlled environment (Git) and an interest in leveraging AI-assisted development tools (like Cursor) to drive efficiency.

• The ability to distill complex findings into executive-ready summaries and visualizations that drive decision-making.

• Fluent in English both written and spoken

• Familiarity with data governance practices (PII handling and access control).

• Experience in Product Analytics or working directly with Product Managers a nice to have

• Familiarity with data engineering concepts (Data Lake, Data Warehouse, ETL / ELT pipeline) and tools (AWS, redshift, Lamdas, Databricks) is a plus