Product Manager – Data Adoption & Monetization

Product Manager – Data Adoption & Monetization

Key Responsibilities:

1.Project Planning and Management:

• Develop and execute project plans, including scope, schedule, resources, and budget, for data-focused projects.
• Define clear project objectives, deliverables, and success criteria in alignment with business goals and technical requirements.

2.Platform Architecture and Technical Oversight:

• Demonstrate working knowledge of data platform components — including ingestion pipelines, data transformation layers, data warehousing, and data serving infrastructure — to guide technical decision-making and backlog prioritization.
• Collaborate with data engineers to shape platform design, ensure scalability and reliability, and drive the delivery of robust, production-grade data infrastructure aligned with business and architectural standards.

3.Stakeholder Coordination and Communication:

• Serve as the primary liaison between technical teams, business users, and other stakeholders.
• Ensure effective communication and alignment across cross-functional teams, translating business needs into technical solution.

4.Risk, Quality, and Performance Management:

• Identify potential risks and implement mitigation strategies to ensure project success.
• Oversee the quality assurance process, ensuring data accuracy, integrity, and reliability throughout the project lifecycle.

5.Performance Monitoring and Continuous Improvement:

• Monitor project performance using advanced analytics tools and methodologies.
• Provide regular updates to stakeholders on project status and outcomes, and implement lessons learned for continuous improvement.

Qualifications:

• Bachelor’s degree in computer science, Information Technology, Data Analytics, or a related field.
• Proven experience in project management, with a strong focus on data engineering and technical projects.
• Solid understanding of data management principles, data governance, and basic programming language (e.g. Python, SQL).
• Proficiency in project management tools (e.g., MS Project, Jira, Asana)
• Excellent communication, technical, and problem-solving skills.
• Experience with cloud platforms (e.g., AWS, Azure) and big data technologies is a plus.