Accelerate your development and exposure to high‑performance data platforms and cloud infrastructure. Join Sedona Digital, a fast‑growing scale‑up with the ambition to be recognized as one of the leading technology companies in Romania. 

Our global client base needs builders, engineers who enjoy designing and implementing scalable data platforms, have deep expertise in cloud data technologies, and take pride in delivering reliable, well‑governed solutions. 

At Sedona, we: 

• Obsess about our customers 
• Build robust, scalable technical solutions 
• Create an open, collaborative culture 
• Invest in learning and long‑term careers 

The Data Product Manager (Premium) is a key role within the Global Data Function, accountable for shaping and delivering the Premium data product as part of the Finance Transformation programme. Working closely with the wider product management team, business stakeholders, Technology delivery teams and Architecture, the role will define the product vision, scope and roadmap required to create a trusted, governed and reusable view of premium data. The product will bring together data from multiple business areas and source systems at a consistent level of detail, establish common definitions and quality standards, and enable consistent reporting, analysis and downstream use. The role will lead discovery across the end-to-end data flow—from source systems and interfaces into the Unified Data Ecosystem through to transformation, conformance and consumption—and make clear, evidence-based decisions on priorities, dependencies and phased delivery. It will also matrix-manage the cross-functional delivery team and partner closely with business owners and subject-matter experts to secure adoption, clear ownership and measurable value. 

Key Responsibilities 

• Product Strategy & Vision: Define and communicate the vision, outcomes and roadmap for the Premium data product, aligned to Finance transformation priorities and wider Group Data strategy. 
• Business Discovery & Scope: Lead discovery with Finance, underwriting and business stakeholders to understand current premium and commission processes, reporting needs, pain points and data flows; translate these into a clear, prioritised and phased product scope. 
• End-to-End Product Ownership: Own the product across source data, interfaces into the Unified Data Ecosystem, transformation and conformance requirements, and interfaces out to dashboards, analytics and other consuming products e.g. planning tooling. 
• Common Data Model: Drive alignment of premium, commission and other data across business areas, including common grain, definitions, dimensions and business rules, while making differences and exclusions explicit. 
• Stakeholder & Business Ownership: Establish effective relationships with senior Finance leaders, business product owners, subject-matter experts, Data, Technology and external partners; secure decisions, sign-off and clear accountability for the product. 
• Roadmap, Prioritisation & Dependencies: Maintain an integrated roadmap and backlog covering source readiness, interfaces, platform capability, transformation, reporting and adoption; expose trade-offs and manage cross-team dependencies. 
• Team Definition & Mobilisation: Define the cross-functional team structure, capabilities, roles and capacity required to deliver the Premium data product once its scope and roadmap are established; identify resource gaps and work with delivery and functional leaders to mobilise the right team for each phase. 
• Cross-Functional Delivery Leadership: Matrix-manage engineering, architecture, data quality, analysis, reporting and testing specialists through discovery, design, build, validation and release, while maintaining clear separation between product outcomes and delivery execution. 
• Data Governance, Quality & Controls: Define ownership, lineage, metadata, access controls, reconciliation and quality expectations so that premium data is trusted, auditable and suitable for authorised use. 
• Adoption & Value Realisation: Define success measures, monitor product health and usage, and work with consumers to embed the product into reporting and decision-making while reducing manual reconciliation and duplicated data preparation. 
• Lifecycle & Operating Model: Agree the transition from change to run, including stewardship, support, small-change prioritisation and ongoing product improvement. 

Requirements 

• Data Product Leadership: Proven experience defining and managing data products from discovery and strategy through delivery, adoption and ongoing stewardship. 
• Commercial & Insurance Acumen: Strong ability to understand how premium data supports financial management, underwriting performance, planning, reporting and executive decision-making. 
• Complex Data Landscape: Experience working across multiple source systems, business units and data models to establish common definitions, aligned grain and reusable data structures. 
• Stakeholder Leadership: Credibility with senior business, Finance, underwriting, Data and Technology stakeholders, with the ability to facilitate decisions, challenge constructively and build alignment where requirements differ. 
• Analytical & Structured Thinking: Ability to break down ambiguous problems, trace business outcomes to source data and transformations, and make pragmatic scope and sequencing decisions. 
• Governance & Data Quality: Practical knowledge of data ownership, controls, lineage, reconciliation, access management and quality standards in a regulated environment. 
• Delivery Leadership: Experience leading cross-functional teams and managing roadmaps, backlogs, risks and dependencies using Agile and appropriate project disciplines. 
• Communication: Excellent written and verbal communication, able to turn complex data and delivery issues into clear choices, recommendations and executive-level updates. 

Nice to Have 

• Experience in commercial or specialty insurance, particularly premium, underwriting, policy, commission or reinsurance data. 
• Understanding of Finance and underwriting reporting, including how premium measures and definitions can vary across business areas and reporting bases. 
• Experience delivering enterprise data products on a cloud data platform and enabling Power BI or comparable analytics consumption. 
• Experience using Jira, Confluence or similar collaboration and delivery-management tools.