.ResponsibilitiesThe Senior Data Product Owner will play a crucial role in the creation and execution of advanced data and AI-driven solutions, working at the intersection of business strategy, technology, and analytics.
This individual will collaborate with cross-functional teams, including engineering, data science, and business stakeholders, to define product roadmaps, prioritize features, and ensure the delivery of high-value, data-centric solutions.
Success in this role requires deep expertise in data analytics, cloud technologies, and product management.Key Responsibilities:Participate in defining the vision, strategy, and roadmap for data products that align with business goals.Prioritize product features based on market needs, business objectives, and technical feasibility.Ensure product alignment with key business stakeholders and engineering teams.Work closely with data scientists, engineers, and business analysts to ensure seamless product delivery.Gather and translate business requirements into detailed product specifications.Facilitate communication and collaboration between technical and non-technical teams.Utilize data analytics to drive product decisions and optimize features.Monitor product performance, user feedback, and market trends to continually improve product offerings.Develop metrics and KPIs to track product success.Oversee the product lifecycle from ideation to release, ensuring on-time delivery and within budget.Lead sprint planning, backlog refinement, and other Agile ceremonies to manage the development process.Mitigate risks and resolve project roadblocks through proactive problem-solving.Conduct market research and competitor analysis to identify opportunities for innovation.Engage with end-users and stakeholders to gather feedback and ensure products meet their needs.Define and communicate a clear value proposition for the product.Essential Qualifications:Proven track record in managing the full lifecycle of data or AI-driven products, from ideation to release.Ability to translate complex business requirements into technical specifications for engineering teams.Experience with Agile methodologies and working in fast-paced, iterative development environments.Strong understanding of cloud platforms, particularly Azure, and their role in supporting data and AI solutions.Familiarity with key technologies, such as Python, Spark, SQL, and Databricks, to effectively guide product development.Experience with ETL processes and data architecture to ensure robust data pipelines.Experience working with both structured and unstructured data to inform product development.Strong analytical mindset with the ability to interpret data insights and drive product decisions based on customer needs and market trends.Demonstrated ability to collaborate across teams, including engineering, sales, and marketing, to drive product success