Product Manager Data & Insights

About Unifonic

Unifonic is a CPaaS (Communication Platform as a Service) company with a team of over 400 professionals, serving more than 5000 customer-centric companies. The Engineering team is responsible for designing, developing, and maintaining the systems and technologies that drive Unifonic’s solutions, collaborating with other departments to meet customer needs. Unifonic has been recognized as a Great Place to Work®.

The Role: 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 champions 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 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 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).
• Influence architectural decisions related to 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.
• Manage 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 for continuous improvement.
• Act as a bridge between technical and non-technical teams, translating business needs into technical requirements.
• Present product updates, reporting insights, and metrics to executives and cross-functional teams.

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 in 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.

AI Proficiency

• Minimum Level: L4 (Proficient) in applying AI across product discovery, specification, prototyping, and stakeholder communication.
• Expected 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.
• Ability to write structured prompts (role, context, constraints, format) and refine prompts rather than manually patching outputs.
• Capable of synthesizing interviews, tickets, and reviews into themes and testable insights, validating each insight against source data.
• Proficient in drafting PRDs, user stories, and executive updates with AI as a first-draft partner, verifying all claims and numbers.
• Understands how AI agents are built (prompts, tools, memory, guardrails) and identifies workflows for automation.
• Awareness of AI risks (hallucination, bias, data privacy, over-reliance) and knowledge of appropriate AI-assisted tasks.

Character Traits

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