Data Product Manager

abra professional services is seeking a Data Product Manager!  We are looking for an experienced Data Product Manager to lead end-to-end data-driven products and solutions. The role includes defining product strategy and roadmap, translating business needs into product requirements, managing priorities and backlog, and collaborating with business stakeholders, Development, Data Engineering, BI, Analytics, and Information Security teams. Responsibilities: Define and lead the vision, strategy, and roadmap for data and analytics products and capabilities. Lead end-to-end development of data-driven products and processes. Identify business needs and translate them into clear, actionable product requirements. Manage the backlog, prioritize tasks, and drive product decision-making. Collaborate with business units, Development, Data Engineering, BI, Analytics, and Information Security teams. Monitor performance and leverage data-driven insights for continuous product improvement. Promote innovation, automation, and advanced use of organizational data assets. Lead the implementation and adoption of solutions and products among end users. Mandatory: Bachelor’s degree in Information Systems, Industrial Engineering and Management, Computer Science, Economics, or a related field. 3–5 years of experience in technology and/or data product management. Proven experience leading complex products end-to-end. Experience working with a wide range of business and technology stakeholders. Ability to define and write business and functional requirements. Understanding of Data, BI, Analytics, and information architecture. Experience working in an Agile environment. Strong analytical skills and a data-driven mindset. Significant Advantage: Significant experience in the mortgage domain, including leading products, processes, or business solutions. Deep understanding of the challenges, processes, and business opportunities in the mortgage industry, with the ability to translate business needs into valuable product solutions. Familiarity with Data Lake, DWH, and enterprise data platforms. Experience working with AI and GenAI solutions. SQL knowledge. Experience leading Self-Service Analytics or Data Platform products.