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Your Tasks The role will be responsible for : Lead end-to-end Manufacturing Data & AI initiatives across factories, from business problem definition and data feasibility assessment through pilot execution, deployment, adoption, and value realization. Build and strengthen AI-ready data foundations by improving data availability, quality, governance, accessibility, KPI standardization, and integration across SAP, MES, Power BI, and shopfloor systems. Translate manufacturing challenges into scalable analytics, AI, automation, and reporting solutions that drive measurable improvements in productivity, cost, quality, capacity utilization, maintenance, and operational performance. Partner closely with Manufacturing, Continuous Improvement, Engineering, Quality, Supply Chain Analytics, and Digital/AI teams to identify opportunities, define requirements, validate use cases, and ensure successful implementation. Develop and validate analytics and AI prototypes using manufacturing data, operational insights, and business expertise to demonstrate feasibility and business value. Manage a portfolio of Manufacturing Data & AI initiatives, ensuring effective prioritization, stakeholder alignment, execution excellence, adoption, and benefit tracking. Establish standardized KPI frameworks, dashboards, benchmarking methodologies, and self-service analytics capabilities to enhance performance visibility, decision-making, and governance. Embed data-driven decision-making, analytics, and AI solutions into factory management systems and Continuous Improvement practices to ensure sustainable outcomes. Serve as the key liaison between manufacturing and technical teams, translating business needs into scalable digital, data, and AI solutions. Drive organizational adoption through communication, training, capability building, and the development of a Manufacturing Data & AI community across the factory network. Your Profile Masters degree in engineering, Industrial Engineering, Information Systems, Data Analytics, Computer Science, or a related discipline. 5+ years of experience in manufacturing, supply chain, operations analytics, digital transformation, or related fields. Strong understanding of manufacturing processes, factory operations, KPI governance, Continuous Improvement, and performance management. Proven experience translating business challenges into analytics, reporting, automation, or AI-driven solutions. Hands-on experience with manufacturing data ecosystems such as SAP ERP, SAP BW/BI, Power BI, MES, Azure Data Platform, and Microsoft technologies. Practical understanding of AI, advanced analytics, automation, and digital manufacturing, with a strong focus on business value and scalable implementation. Good to have: AI/Data Science/Machine Learning certification with hands-on capstone project experience using real-world business or operational data. Strong stakeholder management, communication, adoption, and change management skills in a global and cross-functional environment. Strong analytical and problem-solving mindset with the ability to work hands-on with business and technical teams. Fluent in English and flexible to work in CET time zone At Beiersdorf, we want to help people feel good about their skin and our commitment goes far beyond caring for skin. For 140 years, we have developed innovative skin and body care products for well-known brands such as NIVEA, Eucerin, La Prairie, Hansaplast, and Labello. We act according to our purpose, WE CARE BEYOND SKIN, and take responsibility for our consumers, our employees, the environment and society. Behind every brand, every product and every accomplishment are our more than 20,000 employees. It is for them that we live an inclusive culture of respect and trust that is strongly aligned with our values CARE, COURAGE, SIMPLICITY and TRUST. We also embrace diversity by valuing the uniqueness of each individual and being committed to equal opportunities for all. Additional Information Your responsible recruiter isKalyani Deshmukh .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.