.**Responsibilities**:The Senior Product Owner will drive the strategy, development, and delivery of data-focused products within the organization. This individual will work closely with a cross-functional team to define product roadmaps, prioritize features, and ensure the successful implementation of data-centric solutions. As the key person responsible for managing the product lifecycle, the Senior Product Owner will gather business requirements, analyze market needs, and work with engineering teams to deliver high-value data products. This role requires strong data analytics experience, familiarity with cloud-based technologies, and a proven ability to manage the development process from conception to release.**Accountabilities**:- Define and execute product strategy for data-focused products in collaboration with key stakeholders.- Own the product lifecycle, from ideation and market research to delivery and ongoing optimization.- Prioritize features and build product roadmaps based on business goals, customer feedback, and technical constraints.- Serve as the main point of contact for the engineering team, ensuring alignment between product goals and technical execution.- Collaborate with engineers to ensure data pipelines and analytics tools are designed with scalability and security in mind.- Analyze product performance metrics and implement data-driven improvements to enhance product value.**Essential Job Functions and Requirements**:- Product Management Experience_:_- Proven experience in managing the full lifecycle of data products, from concept to delivery.- Strong ability to translate business requirements into technical specifications and actionable tasks for engineering teams.- Familiarity with Agile methodologies and experience with iterative product development.- Technical Expertise:_- Familiarity with Databricks for managing data pipelines and analytics processes.- Understanding of Python, Spark, and SQL to effectively communicate with engineers and guide technical decisions.- Knowledge of various ETL techniques (e.G., batch processing, stream processing) and examples of how they are used in product delivery.- _Data Experience:_- Experience working with structured data (e.G., databases, CSV files) and unstructured data (e.G., JSON, logs).- Ability to understand data models, analytics, and the challenges of working with large datasets.- Data Analytics & Market Research:_- Proven ability to analyze data and interpret trends to drive product decisions.- Experience working with analytics tools (e.G., Power BI, Tableau) to evaluate product performance and customer insights.- DevOps & CI/CD:_- Familiarity with continuous integration and continuous delivery practices to support efficient and rapid deployment of product updates.- Experience working with Azure DevOps to manage product releases, track work items, and support engineering workflows