Product Manager Data & Insights

About Unifonic

Unifonic is a CPaaS (Communication Platform as a Service) company based in Riyadh, Riyadh Province, recognized as a Great Place to Work®. The company focuses on business communication solutions, supported by a team of over 400 employees serving more than 5000 customer-centric companies. Unifonic fosters a collaborative work environment that encourages creativity.

The Role of Product Manager - Data & Insights

Unifonic is seeking a Product Manager - Data & Insights for a full-time position. This role involves leading the development of both customer-facing dashboards and internal reporting systems. The Product Manager will be responsible for the end-to-end product lifecycle for reporting capabilities, from customer research and data modeling to delivery, governance, and continuous improvement. This position requires 5-10 years of experience and involves close collaboration with data engineers, analysts, UX teams, and business stakeholders to build a robust data ecosystem.

Key Responsibilities

• Define and execute the roadmap for customer-facing analytics, reporting portals, and internal reporting infrastructure.
• Align reporting solutions with business goals and customer needs.
• Collaborate with leadership to prioritize initiatives based on impact, complexity, and business value.
• Act as an advisor for other Product teams in data strategy and design.
• Collect business and technical requirements from cross-functional stakeholders, including Finance, Operations, Customer Success, Product, and Engineering.
• Develop detailed feature requirements, user stories, acceptance criteria, and data contracts for reporting systems.
• Translate ambiguous business questions into well-defined reporting needs and KPIs.
• Partner with data engineers to co-develop data models and data marts in the data warehouse (*, Snowflake, Qlik, Vertica).
• Understand schema design and its impact on performance, usability, and extensibility of data reporting systems.
• Influence architectural decisions around extract-transform-load (ETL/ELT) processes and dimensional modeling.
• Own and enforce data governance standards, including data definitions, taxonomy, lineage, and version control.
• Define processes for data quality verification and anomaly detection in collaboration with engineering and analytics teams.
• Advocate for data accuracy and monitor for misleading or incomplete insights.
• Own the product experience and lifecycle for reporting and BI platforms (*, Looker, Tableau, Power BI, Sigma, or Mode).
• Define self-service analytics capabilities for internal teams.
• Create feedback loops to continually improve dashboard usability and relevance for both internal and external users.
• Act as the bridge between technical and non-technical teams, translating business needs into technical requirements and vice versa.
• Present product updates, reporting insights, and metrics to executives and cross-functional teams.
• Facilitate decision-making on trade-offs related to data availability, accuracy, and reporting timelines.

Required Qualifications and Skills

• 5-10 years of experience in a relevant field.
• Experience applying AI across product discovery, specification, prototyping, and stakeholder communication.
• Ability to use AI to speed up research, specifications, and prototyping, while personally owning the accuracy of every output.
• Hands-on experience with Claude and Lovable.
• Proficiency in writing structured prompts (role, context, constraints, format) and refining prompts rather than manually patching outputs.
• Ability to synthesize interviews, tickets, and reviews into themes and testable insights, validating every insight against source data.
• Experience drafting PRDs, user stories, and executive updates with AI as a first-draft partner, then verifying every claim and number.
• Skill in building clickable prototypes in Lovable to validate ideas with stakeholders, with clear understanding that prototypes are not production-ready.
• Understanding of how AI agents are built (prompts, tools, memory, guardrails) and proactive identification of workflows suitable for automation.
• Awareness of AI risks (hallucination, bias, data privacy, over-reliance) and knowledge of what should and should not be AI-assisted.

Desired Character Traits

• Analytical thinking and problem-solving skills.
• Strong sense of ownership and accountability.
• Effective communication across teams.
• Collaborative work ethic.
• Adaptability and a commitment to continuous learning.
• Mentorship and knowledge sharing capabilities.
• Resilience under pressure and constructive handling of setbacks.
• High standards for quality and attention to detail.
• Advocacy for best practices, efficiency, and innovation.