As a Product Manager, Data & Insights, you will lead the development of both customer-facing dashboards and internal reporting systems. This role sits at the intersection of product management, data engineering, and analytics, responsible for delivering intuitive, reliable, and scalable reporting experiences for both external users and internal stakeholders.
You will own the end-to-end product lifecycle for reporting capabilities—from customer research and data modeling through to delivery, governance, and continuous improvement. You will partner closely with data engineers, analysts, UX teams, and business stakeholders to build a robust data ecosystem that enables self-service analytics, supports compliance requirements, and delivers meaningful insights for executive decision-making.
You will also champion and lead data compliance initiatives across all Unifonic products, ensuring that data is managed responsibly, securely, and in alignment with organizational and regulatory requirements.
Help us shape the future of communication by:
- Defining and executing 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. Be an advisor for other Product teams in data strategy and design.
- Collecting business and technical requirements from cross-functional stakeholders, including Finance, Operations, Customer Success, Product, and Engineering.
- Developing detailed feature requirements, user stories, acceptance criteria, and data contracts for reporting systems. Translate ambiguous business questions into well-defined reporting needs and KPIs.
- Partnering closely with data engineers to co-develop data models and data marts in the data warehouse (e.g., Snowflake, Qlik, Vertica). Understand schema design and how it impacts performance, usability, and extensibility of data reporting systems. Influence architectural decisions around extract-transform-load (ETL/ELT) processes and dimensional modeling.
- Owning and enforcing data governance standards, including data definitions, taxonomy, lineage, and version control.
- Defining processes for data quality verification and anomaly detection in collaboration with engineering and analytics teams. Be an advocate for data accuracy and a watchdog for misleading or incomplete insights.
- Owning the product experience and lifecycle for reporting and BI platforms (e.g., Looker, Tableau, Power BI, Sigma, or Mode).
- Defining self-service analytics capabilities for internal teams. Create feedback loops to continually improve dashboard usability and relevance for both internal and external users.
- Acting 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.
What you’ll bring:
- 5+ years of experience in product management, data, analytics, or reporting platforms, with a strong 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, 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 a plus.
- Understanding of data quality, data integrity, scalability, and performance considerations when building 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.
- Bachelor’s degree in Computer Science, Data Science, Business, Engineering, or a related field
AI Proficiency:
- Minimum Level:L4 (Proficient). Applies AI across product discovery, specification, prototyping, and stakeholder communication.
- Expected: Uses AI to speed up research, specs, and prototyping, and personally owns the accuracy of every output.
- Hands-on experience with Claude and Lovable. Writes structured prompts (role, context, constraints, format) and refines the prompt rather than patching outputs by hand.
- Synthesizes interviews, tickets, and reviews into themes and testable insights, and validates every insight against source data before sharing.
- Drafts PRDs, user stories, and executive updates with AI as a first-draft partner, then verifies every claim and number before it reaches leadership.
- Builds clickable prototypes in Lovable to validate ideas with stakeholders, and is clear that a prototype is not production-ready.
- Understands how AI agents are built (prompts, tools, memory, guardrails) and proactively identifies workflows worth automating.
- Flags AI risks (hallucination, bias, data privacy, over-reliance) and knows what should and shouldn't be AI-assisted.
Craft and Toolkit:
- Strong SQL and data analysis skills.
- Experience with data warehouses such as Snowflake, ClickHouse, or Vertica.
- Knowledge of data modeling, dimensional modeling, data marts, and data pipelines.
- Experience with BI and reporting tools such as Looker, Tableau, Power BI, Sigma, or Metabase.
- Understanding of ETL/ELT, dbt, and data orchestration.
- Knowledge of data governance, quality, lineage, and compliance.
- Understanding of GDPR, PDPL, and data privacy principles.
- 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 – approach problems clearly, use data, and find solutions.
- Ownership and accountability – take responsibility and follow projects through to completion.
- Communication – explain ideas clearly and listen to others across teams.
- Collaboration – work well with others and support team goals.
- Adaptability and learning – adjust to change and keep learning new skills or tools.
- Mentorship and knowledge sharing – help others grow and share what you know.
- Resilience – stay calm under pressure and handle setbacks constructively.
- Quality and attention to detail – do work carefully and strive for improvement.
- Advocacy and innovation – encourage best practices, efficiency, and new ideas
