Product Data Analyst (L3)

About the job

This position is needed to help uncover and deliver product data, analysis, and insights that empower stakeholders at all levels to maximize the impact of data in decision making. Our team is expanding to provide meaningful, data-backed insights from which to develop and grow our industry leading communications products. You will own analytics workstreams end to end from ambiguous problem statements to deliver insights in a fast moving environment.

Responsibilities

In this role, you’ll:

• End-to-End Analytics: Own complex projects from scoping ambiguous problems to delivering actionable, data-driven insights.
• Product Strategy: Partner with PMs to define metrics, build reporting dashboards, and inject data into product planning.
• Technical Execution: Apply SQL and visualization tools (Looker, Tableau) to translate complex data into clear stakeholder recommendations.
• Data Standardisation: Maintain and document metrics, datasets, and models using Confluence and Datahub to ensure a single source of truth.
• Project Management: Balance multiple concurrent initiatives with clear prioritization and proactive status updates.
• Quality Assurance: Maintain rigorous data quality standards through robust validation and transparent quality control.
• AI-Driven Efficiency: Integrate modern AI tools into daily workflows to speed up SQL coding, analysis, and documentation.

Qualifications

Required:

• Professional Experience: 4+ years of experience in quantitative analysis, business intelligence, or data analytics, with a proven track record of converting complex, ambiguous data into actionable business results.
• Core Technical Skills: 4+ years of hands-on experience writing, optimizing, and performing quality assurance (QA) in SQL or relational database languages on a regular basis.
• Data Visualization: Proficiency with modern BI tools, with a strong preference for Tableau and Looker (LookML).
• Structured Problem Solving: Strong analytical mindset with the ability to decompose vague problem statements into clear, executable data strategies.
• End-to-End Ownership: Demonstrated ability to independently manage deliverables from initial requirement gathering through to stakeholder presentation.