Data Analytics Product Manager

Job Description

Your Role

The Data Services and Solutions team is responsible for the technical design and end-to-end delivery of complex, data-driven solutions and products across the enterprise. We are looking for a seasoned professional who brings a strong combination of deep technical expertise and product ownership, with proven experience in delivering complex data solutions. This position reports to the Sr. Manager, Data Services and Solutions and will partner closely with Enterprise Architecture, Portfolio, Analytics, and Data Engineering teams. If you thrive in a fast-paced environment, have a passion for data innovation, and bring a strong blend of product ownership and technical solutioning skills, we’d love to hear from you.

Your Work

In this role, you will :

• Lead product strategy and roadmap development for enterprise data products, translating business needs into actionable technical requirements and user stories.
• Collaborate with cross-functional teams to define use cases, prioritize features, and drive delivery using agile methodologies including sprint planning and backlog grooming.
• Architect and design scalable cloud-based data solutions including data lakes, data warehouses, and data marts.
• Provide technical leadership in solution design, risk mitigation, and issue resolution across on-prem, cloud, and hybrid ecosystems.
• Champion best practices in cloud architecture, data infrastructure cost optimization, and DevOps automation.
• Maintain and evolve technology inventories, reference models, standards, and usage guidelines.
• Evangelize data and analytics capabilities across business and IT teams, fostering a culture of innovation and data-driven decision-making.
• Monitor and optimize data product performance, identifying opportunities for enhancement and scalability.
• Work closely with engineering and analytics teams to ensure timely, high-quality delivery of data solutions.
• Apply CI / CD practices and automation across documentation, testing, build, deployment, configuration, and monitoring.
• Partner with portfolios to define technical requirements, principles, and models that guide data solution decisions.
• Use comprehensive analytical thinking to assess time-to-market, cost impact, and business value across people, process, and technology.

Your Knowledge and Experience