Externally this role could also be known as: Data Product Owner, Data Product Manager, Product Owner, Product Manager
Over recent years NewDay has been on an exciting journey of growing it’s Product organisation and ensuring that our teams are at the heart of change within the business. The next stage of our Product evolution is to align our data capabilities within Product, which this role will do. The Data Platforms Product Owner role will be aligned to a domain area and lead a team of Data Engineers. The Data Platforms Product Owner will be partnering with upstream engineering teams and downstream data consumers to create data sets and deliver data solutions to enable model execution, business analytics and regulatory and business reporting.
You will be a shining example of Product excellence, setting the Product vision, Roadmap and OKRs for the team and balancing the needs of the business and our customers. This is an exciting time to join NewDay as we build out our platform business whilst continuing to support wider company needs. This role will allow you to shape the way data can truly contribute to the next evolution of the business.

WHAT WILL YOU BE DOING DAY-TO-DAY?

• Product Roadmap & Backlog Management: Create, maintain, and prioritise the roadmap to deliver value from data assets to our internal consumers and external clients.
• Vision and Strategy: Define the vision and strategy for your product ensuring it aligns to the wider Data Product Vision and strategic objectives
• Stakeholder Management: Engage with key internal and external stakeholders to understand their data and reporting needs, translate those needs into clear and well-defined product requirements and user stories.
• Sprint Planning and Execution: Lead in collaboration with your data engineering lead for all sprint ceremonies (sprint planning, daily stand-ups, refinements, sprint reviews, and retrospectives).
• Data Governance and Quality: Collaborate with relevant teams to ensure data quality, integrity, and adherence to data governance policies and regulatory requirements.
• Product Performance: Define OKRs to measure and evaluate the performance of your data products.
• Product Adoption: Drive the adoption of your data products, promoting data literacy across the company making sure that the product and any related assets remain relevant to your users.
• Collaboration: Orchestrate collaboration between diverse teams, fostering communication between data scientists, engineers, analysts, and business stakeholders.