Product Manager Data & Insights

About Unifonic

Unifonic is a CPaaS (Communication Platform as a Service) company with a team of over 400 employees, serving more than 5000 customer-centric companies. The company has been recognized as a Great Place to Work® and operates with a focus on collaboration and innovation.

The Role of Product Manager - Data & Insights

Unifonic is seeking a Product Manager - Data & Insights to lead the development of both customer-facing dashboards and internal reporting systems. This full-time position is based in Riyadh, Riyadh Province, and requires 5-10 years of experience. The role involves managing the end-to-end product lifecycle for reporting capabilities, from customer research and data modeling to delivery, governance, and continuous improvement. The Product Manager will collaborate with data engineers, analysts, UX teams, and business stakeholders to build a robust data ecosystem that supports self-service analytics, compliance, and executive decision-making. This role also includes championing data compliance initiatives across all Unifonic products.

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, prioritizing initiatives based on impact, complexity, and business value.
• Advise other Product teams on 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 data warehouses (*, Snowflake, Qlik, Vertica).
• Understand schema design and its impact on performance, usability, and extensibility of data reporting systems.
• Influence architectural decisions related to 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 and create feedback loops to improve dashboard usability and relevance.
• Act as a 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

• Proven experience delivering customer-facing reporting products, dashboards, and internal analytics solutions.
• Strong understanding of data privacy, governance, and compliance frameworks, including GDPR and PDPL.
• Experience working cross-functionally with data engineers, analysts, product teams, UX, and business stakeholders.
• Hands-on experience with data warehouses such as ClickHouse, Vertica, or Snowflake, and BI tools such as Metabase, Tableau, Looker, Power BI, or Sigma.
• Strong SQL skills and a solid understanding of data modeling concepts, including fact and dimension tables and star schemas.
• Familiarity with ELT pipelines, dbt, and data orchestration tools is beneficial.
• Understanding of data quality, data integrity, scalability, and performance considerations for reporting solutions.
• Ability to define business KPIs and translate business and reporting needs into clear data and product requirements.
• Experience contributing to data governance, data integrity, and compliance initiatives.
• Ability to balance performance, usability, scalability, and cost when designing data and reporting solutions.
• Strong communication and stakeholder management skills, with the ability to translate complex data concepts into clear business requirements and insights.
• Proven ability to lead cross-functional discussions, align stakeholders around data strategy, and communicate reporting goals and insights effectively.

AI Proficiency (Minimum Level: L4 - Proficient)

• Applies AI across product discovery, specification, prototyping, and stakeholder communication.
• Uses AI to accelerate research, specifications, and prototyping, while personally ensuring the accuracy of all outputs.
• Hands-on experience with Claude and Lovable.
• Writes structured prompts (role, context, constraints, format) and refines prompts rather than manually patching outputs.
• Synthesizes interviews, tickets, and reviews into themes and testable insights, validating each insight against source data.
• Drafts PRDs, user stories, and executive updates with AI as a first-draft partner, verifying all claims and numbers before leadership review.
• Builds clickable prototypes in Lovable to validate ideas with stakeholders, clearly indicating that prototypes are not production-ready.
• Understands how AI agents are built (prompts, tools, memory, guardrails) and proactively identifies workflows suitable for automation.
• Identifies and flags AI risks such as hallucination, bias, data privacy, and over-reliance, understanding what should and should not be AI-assisted.

Desired Character Traits

• Analytical thinking and problem-solving: Approaching problems clearly, utilizing data, and finding solutions.
• Ownership and accountability: Taking responsibility and ensuring project completion.
• Communication: Explaining ideas clearly and actively listening across teams.
• Collaboration: Working effectively with others and supporting team goals.
• Adaptability and learning: Adjusting to change and continuously acquiring new skills or tools.
• Mentorship and knowledge sharing: Supporting the growth of others and disseminating knowledge.
• Resilience: Maintaining composure under pressure and handling setbacks constructively.
• Quality and attention to detail: Executing work carefully and striving for continuous improvement.
• Advocacy and innovation: Encouraging best practices, efficiency, and new ideas.