Job Title: Manager - Data Collection Engineering
Location: Bangalore
About Unilever:
Be part of the world\xe2\x80\x99s most successful, purpose-led business. Work with brands that are well-loved around the world, that improve the lives of our consumers and the communities around us. We promote innovation, big and small, to make our business win and grow; and we believe in business as a force for good. Unleash your curiosity, challenge ideas and disrupt processes; use your energy to make this happen. Our brilliant business leaders and colleagues provide mentorship and inspiration, so you can be at your best. Every day, nine out of ten Indian households use our products to feel good, look good and get more out of life \xe2\x80\x93 giving us a unique opportunity to build a brighter future.
Every individual here can bring their purpose to life through their work. Join us and you\xe2\x80\x99ll be surrounded by inspiring leaders and supportive peers. Among them, you\xe2\x80\x99ll channel your purpose, bring fresh ideas to the table, and simply be you. As you work to make a real impact on the business and the world, we\xe2\x80\x99ll work to help you become a better you.
Business Context:
Unilever is a business founded in 1890s with a strong belief in social purpose, and our unique heritage still shapes the way we do business today.
We are one of the world\'s leading consumer goods companies, making and selling around 400 brands in more than 190 countries, \xe2\x82\xac51B in revenues and a global presence across Europe, Americas, and Asia/AMET/RUB. Over 2.5 billion people use our products to feel good, stay healthy and make their lives easier. That\'s about a third of the global population choosing from household names such as Lipton, Knorr, Dove and Hellmann\'s, and local brands like Bango in Indonesia and Suave in the US.
Unilever\xe2\x80\x99s Purpose is to make sustainable living commonplace, and this is underpinned by The Unilever Compass: Purpose-Led, Future-Fit is our new, single growth strategy based on three beliefs; Brands with purpose grow, Companies with purpose last, People with purpose thrive. Our vision is to be the global leader in sustainable business. We will demonstrate how our purpose-led, future-fit business model drives superior performance, consistently delivering financial results in the top third of our industry.
Our sustainable living brands are inspiring people because they do good for society, environment, and contribute to the UN Sustainable Development Goals. Our sustainable living brands grew 46% faster than our other brands and accounted for 70% of total growth.
Background
As the Lead for Data Collection Engineering Lead you will be responsible for ensuring that CEP (Consumer Engagement) and CX collect data points that enable analytics capabilities across Unilevers owned properties.
Your role is instrumental in ensuring consistent and thorough analytics capabilities that enable Unilever to collect relevant first party and third-party information to help drive its data and audience/personalisation ambitions in a consistent, safe and secure manner.
Building strong partnerships with your Corporate Centre and Business Group colleagues is a must as you will play an invaluable part in translating requirements and solutions from across Unilever and UniOps. You\xe2\x80\x99ll need to be aware of the everchanging consumer and technical landscape and consider their effects on the analytics data collection space. You must view the long-term use of the products and ensure you deliver for scalability and adaptability into the solutions from day one.
As the Data Collection Engineering Lead, you\xe2\x80\x99ll be a key driver of analytics development in the Consumer Experience team \xe2\x80\x93 raising the floor in terms of the analytics understanding our community has. You have a responsibility to contribute to the team\xe2\x80\x99s culture and drive positive change, ensuring analytics is front and centre of all projects and architecture ensuring the principles align with Unilever\xe2\x80\x99s cultural values.
Job Summary
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