Digital project manager in data platforms

Описание:Schneider Digital is the digital department of Schneider Electric, leading the digital transformation in the company by giving support globally to our internal teams and our clients. Schneider Digital consists of 6 Digital Hubs worldwide which are strategically located to ensure a 24/7 support across the company (France, China, India, USA, Mexico and Spain). Our Digital Hub in Barcelona is formed by +450 employees working in strategic projects and different roles such as Data, Cybersecurity, ERP, Cloud, Infrastructures, IT Project Management or Digital Marketing. We are looking for a motivated, high-potential professional to join the Data PMO as a Lead, Digital Project Manager.Задачи:Manage and coordinate assigned Data PMO initiatives, from planning and execution through monitoring, reporting, and closure, with an appropriate level of guidance based on complexity. Maintain project plans, milestones, actions, dependencies, RAID logs, decisions, and deliverables, ensuring clear ownership and timely follow-up. Coordinate contributors across Data, IT, business, and other functions to keep activities aligned and issues moving toward resolution. Identify delivery risks, slippage, dependencies, and decisions required; escalation early with a clear summary of impact and recommended next steps. Apply PMO standards and fit-for-purpose project management methods, while continuously improving the structure and quality of project execution. Apply fit-for-purpose delivery approaches, including Agile, Scrum, Waterfall, or Hybrid methods, according to the needs and governance of each initiative. Where appropriate, facilitate Agile team practices such as sprint planning, daily stand-ups, reviews, retrospectives, and backlog or action follow-up; help surface blockers and keep commitments visible. Build constructive working relationships with project stakeholders and maintain clear, concise, and proactive communication. Prepare project updates, management presentations, dashboards, meeting materials, and decision summaries tailored to the audience. Facilitate meetings and working sessions, clarify actions and accountabilities, and follow through to secure outcomes. Work effectively in a global, matrixed environment, adapting to different working styles, cultures, and time zones. Demonstrate the confidence to ask questions, clarify ambiguity, challenge constructively, and raise concerns professionally. Develop, maintain, and improve project and portfolio reporting, KPIs, dashboards, and management information. Use data analysis to identify trends, inconsistencies, risks, and opportunities for improved portfolio visibility and decision-making. Support data quality, consistency, and governance across project information and PMO tools. Build familiarity with data platforms, analytics concepts, and the terminology used by Data & Technology teams, enabling effective coordination and communication. Actively explore and apply approved AI tools, automation, and analytics to improve project planning, reporting, meeting outputs, action tracking, and risk visibility. Identify repetitive or manual PMO activities that could be simplified, then test and implement practical improvements with appropriate stakeholder alignment. Validate AI-generated outputs for accuracy, relevance, confidentiality, and bias; apply professional judgment and remain accountable for final deliverables. Share effective practices and lessons learned, contributing to reusable solutions rather than isolated automations. Demonstrate a growth mindset by continuously developing AI literacy and relevant project management, data, and analytical skills. Maintain reliable project documentation, status information, and governance records in the relevant enterprise tools. Support consistent application of PMO processes, templates, reporting standards, and control requirements. Track agreed effort, costs, budgets, or financial information where required for assigned initiatives, ensuring accuracy and timely escalation of variances. Help translate complex information into structured options, clear actions, and practical recommendations.Требования:Bachelor’s degree in Engineering, Computer Science, Information Technology, Data/Analytics, Business, or a related discipline. Foundational understanding of project management practices, including planning, milestones, dependencies, risks, issues, actions, and status reporting. Familiarity with Agile principles and Scrum practices; awareness of SAFe or other scaled Agile approaches used in larger enterprise environments. Comfortable working with data, spreadsheets, dashboards, and structured information; experience with Power BI, Jira, Excel, or similar tools is an advantage. Interest in data platforms, analytics, and digital technologies; deep engineering expertise is not required, but the ability and motivation to learn relevant terminology are important. Practical interest in Generative AI, automation, and AI-enabled workflo