الوصف الوظيفي
Looking for challenging role? If you really want to make a difference - make it with us At Siemens Energy India Limited, we are more than just an energy technology company. We develop the energy systems of the future, ensuring that the growing energy demand of the global community is met reliably and sustainably. The technologies created in Siemens Energy’s research departments and factories drive the energy transition and provide the base for one sixth of the world's electricity generation. Siemens Energy’s global team is committed to making sustainable, reliable, and affordable energy a reality by pushing the boundaries of what is possible. We uphold a 150-year legacy of innovation that encourages our search for people who will support our focus on decarbonization, new technologies, and energy transformation. Y our new role – challenging and future-oriented We are looking for a dynamic Talent and Learning Professional to support the design, integration, and ongoing evolution of the SEIL’s talent, learning, and succession architecture. Working closely with senior leaders, HR Business Partners, and global teams, the role contributes to shaping talent identification, succession planning, learning ecosystems, and culture ‑ linked capability building. The role requires strong conceptual thinking, the ability to translate insights into practical solutions, and skill in influencing and aligning stakeholders within a complex, global environment. The role reports directly to the Head, Talent and Learning of Siemens Energy India Limited and is based in Gurugram, Haryana. How You’ll Make an Impact Talent and Learning Architecture • Support the development and maintenance of the overall talent and learning architecture, including talent identification approaches and assessment formats. • Contribute to understanding business and organizational requirements to ensure talent and learning solutions remain relevant and future focused. • Support effective adoption and application of global talent and learning frameworks, adapting them thoughtfully to local context. Succession Planning and Talent Pipelines • Plan and facilitate organization wide succession planning discussions. Assist in building and maintaining succession pipelines for critical roles, including readiness assessments and gap identification. • Provide analytical inputs and insights on talent depth, risks, and pipeline health to support informed decision making. • Drive programs to reinforce a consistent and shared understanding of talent, performance, and potential across stakeholders. Learning Ecosystem Management • Support the transition from current state learning approaches to future state solutions, including alignment with Siemens Energy learning platforms and systems. • Help ensure learning investments are aligned to identified talent and capability needs. • Partner with senior leaders and HR Business Partners to support alignment of talent and learning initiatives with business priorities. OD and Culture Integration • Contribute to organization development and cultural alignment initiatives, including capability building and leadership behavior reinforcement. • Help embed cultural and leadership expectations within talent and learning frameworks and programs. What you bring: • Degree in Human Resources Management • 6 - 8 years of progressive experience in talent management, succession planning, learning, leadership development, or organization development. • Strong conceptual and systems thinking capability, with experience designing integrated talent and learning frameworks. • Demonstrated ability to engage and influence senior leaders in talent and succession discussions. • Experience working within global or matrixed organizations and partnering with global COEs. Ability to navigate complex stakeholder environments • Strong analytical capability, with experience using insights and data to inform talent and learning decisions. • Ability to balance strategic design with practical execution and stakeholder alignment.
لقد تمت ترجمة هذا الإعلان الوظيفي بواسطة الذكاء الاصطناعي وقد يحتوي على بعض الاختلافات أو الأخطاء البسيطة.
