Product Manager Data & Insights

About Unifonic and the Role

Unifonic, recognized as a Great Place to Work®, operates in the CPaaS sector, focusing on business communication solutions. The company's engineering team is responsible for designing, developing, and maintaining the systems that support Unifonic’s offerings. This full-time Product Manager - Data & Insights role is based in Riyadh, Riyadh Province, and involves leading the development of both customer-facing dashboards and internal reporting systems.

Role Overview

The Product Manager, Data & Insights, will manage the end-to-end product lifecycle for reporting capabilities, from customer research and data modeling to delivery, governance, and continuous improvement. This position requires collaboration with data engineers, analysts, UX teams, and business stakeholders to establish a robust data ecosystem. The role also includes championing data compliance initiatives across all Unifonic products, ensuring data management aligns with organizational and regulatory requirements.

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.
• Advise other Product teams on data strategy and design.
• Collect business and technical requirements from cross-functional stakeholders.
• Develop detailed feature requirements, user stories, acceptance criteria, and data contracts for reporting systems.
• Translate business questions into defined reporting needs and KPIs.
• Partner with data engineers to co-develop data models and data marts in the data warehouse.
• Understand schema design and its impact on performance, usability, and extensibility of data reporting systems.
• 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.
• Advocate for data accuracy and monitor for misleading or incomplete insights.
• Own the product experience and lifecycle for reporting and BI platforms.
• Define self-service analytics capabilities for internal teams.
• Create feedback loops to improve dashboard usability and relevance.
• Act as a liaison between technical and non-technical teams.
• 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.

Qualifications and Requirements

• Experience: 5-10 years in product management, data, analytics, or reporting platforms, with a focus on data-driven products.
• Proven experience delivering customer-facing reporting products, dashboards, and internal analytics solutions.
• Strong understanding of data privacy, governance, and compliance frameworks (*, GDPR, PDPL).
• Experience working cross-functionally with data engineers, analysts, product teams, UX, and business stakeholders.
• Hands-on experience with data warehouses (*, ClickHouse, Vertica, Snowflake) and BI tools (*, Metabase, Tableau, Looker, Power BI, Sigma).
• Strong SQL skills and understanding of data modeling concepts (fact and dimension tables, star schemas).
• Familiarity with ELT pipelines, dbt, and data orchestration tools is beneficial.
• Understanding of data quality, 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, integrity, and compliance initiatives.
• Ability to balance performance, usability, scalability, and cost in data and reporting solution design.
• Strong communication and stakeholder management skills.
• Proven ability to lead cross-functional discussions and align stakeholders on data strategy.
• Education: Bachelor’s degree in Computer Science, Data Science, Business, Engineering, or a related field.

AI Proficiency and Technical Skills

• AI Proficiency (Level 4 - Proficient): Applies AI across product discovery, specification, prototyping, and stakeholder communication. Uses AI for research, specs, and prototyping, while personally owning the accuracy of all outputs. Experience with Claude and Lovable, including writing structured prompts and refining them. Synthesizes insights from various sources, validating against source data. Drafts PRDs, user stories, and executive updates with AI as a first-draft partner, verifying all claims. Builds clickable prototypes in Lovable. Understands AI agent construction and identifies automation workflows. Flags AI risks such as hallucination, bias, data privacy, and over-reliance.
• Craft and Toolkit: Strong SQL and data analysis skills. Experience with data warehouses (Snowflake, ClickHouse, Vertica). Knowledge of data modeling, dimensional modeling, data marts, and data pipelines. Experience with BI and reporting tools (Looker, Tableau, Power BI, Sigma, Metabase). Understanding of ETL/ELT, dbt, and data orchestration. Knowledge of data governance, quality, lineage, and compliance, including GDPR and PDPL. Ability to define KPIs, data requirements, data contracts, and reporting specifications. Understanding of scalable, performant, and cost-effective reporting architectures.

Character Traits

• Analytical thinking and problem-solving.
• Ownership and accountability.
• Effective communication across teams.
• Collaboration and support for team goals.
• Adaptability and continuous learning.
• Mentorship and knowledge sharing.
• Resilience under pressure.
• Commitment to quality and attention to detail.
• Advocacy for best practices and innovation.