Product Data Manager

We are seeking an experienced Data Product Manager to lead the strategy, roadmap, and delivery of enterprise data products on Google Cloud Platform (GCP). The role will focus on maximizing business value from data assets by partnering with stakeholders across Network, Technology, Digital, and Business teams while working closely with Data Engineering, Analytics, Governance, and Architecture teams.

The ideal candidate combines strong product management capabilities, data and analytics expertise, stakeholder management, and a deep understanding of modern cloud data ecosystems.

Key Responsibilities

• Define and own the vision, strategy, roadmap, and lifecycle for data and analytics products.
• Gather, analyze, and prioritize business requirements from stakeholders across multiple domains.
• Translate business needs into product requirements, epics, features, and user stories for engineering teams.
• Drive development and adoption of data products, dashboards, APIs, self-service analytics, and data platforms.
• Collaborate with Data Engineers, Solution Designers, Architects, Analysts, and Data Scientists to deliver scalable solutions.
• Establish and track product KPIs, customer adoption metrics, business value realization, and product performance.
• Manage and prioritize product backlogs, release planning, and delivery milestones in Agile environments.
• Ensure alignment with enterprise data governance, security, privacy, and compliance requirements.
• Promote data quality, metadata management, lineage, and stewardship across products.
• Lead stakeholder workshops, product discovery sessions, and roadmap reviews.
• Identify opportunities for automation, operational efficiency, and enhanced customer experiences through data.
• Drive change management, communication, and user adoption initiatives for delivered solutions.
• Manage dependencies across teams and proactively address delivery risks.

Must Have Skills & Experience

• 8+ years of experience in Product Management, Data & Analytics, Business Intelligence, or related domains.
• Proven experience managing and delivering enterprise-scale data products and analytics solutions.
• Strong understanding of modern data platforms, data lakes, data warehouses, and cloud-native data architectures.
• Experience working with Google Cloud Platform (GCP) services such as:
• BigQuery
• Pub/Sub
• Dataflow
• Strong understanding of data engineering concepts, ETL/ELT pipelines, data integration, and analytics ecosystems.
• Experience defining product roadmaps, business cases, prioritization frameworks, and success metrics.
• Hands-on experience working within Agile/Scrum delivery frameworks.
• Strong stakeholder management and executive communication skills.
• Experience with data governance, security, compliance, and data quality frameworks.
• Ability to translate complex business requirements into actionable technical product requirements.
• Strong analytical, problem-solving, and decision-making capabilities.

Nice to Have

• Experience in Telecommunications, Network Analytics, or Digital Transformation programs.
• Knowledge of AI/ML solutions, predictive analytics, and data science product delivery.
• Familiarity with Kafka, event streaming platforms, and real-time analytics solutions.
• Understanding of data cataloging, metadata management, and governance tools.
• Experience with multi-cloud environments (AWS and Azure).
• Exposure to API products, self-service analytics platforms, and data monetization initiatives.
• Product Management certifications such as:
• SAFe Product Manager/Product Owner
• Pragmatic Product Management
• GCP certifications and data-related cloud certifications.
• Product Strategy and Roadmap Management
• Stakeholder and Executive Management
• Data and Analytics Domain Knowledge
• Agile Product Delivery
• Business Value Realization
• Customer-Centric Thinking
• Communication and Influencing Skills
• Risk and Dependency Management
• Leadership and Cross-Functional Collaboration
• Data Governance and Compliance Awareness

Success Measures

• Successful delivery of strategic data products aligned with business objectives.
• Increased adoption and usage of data assets and analytics solutions.
• Measurable business outcomes through data-driven decision-making.
• Improved data quality, accessibility, governance, and trust.
• Strong stakeholder satisfaction and value realization from product investments.
• Effective collaboration between business, engineering, and analytics teams.

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