About the job
Ralph Lauren Corporation (NYSE:RL) is a global leader in the design, marketing and distribution of premium lifestyle products in five categories: apparel, accessories, home, fragrances, and hospitality. For more than 50 years, Ralph Lauren’s reputation and distinctive image have been consistently developed across an expanding number of products, brands and international markets. The Company’s brand names, which include Ralph Lauren, Ralph Lauren Collection, Ralph Lauren Purple Label, Polo Ralph Lauren, Double RL, Lauren Ralph Lauren, Polo Ralph Lauren Children, Chaps, among others, constitute one of the world’s most widely recognized families of consumer brands.
At Ralph Lauren, we unite and inspire the communities within our company as well as those in which we serve by amplifying voices and perspectives to create a culture of belonging, ensuring inclusion, and fairness for all. We foster a culture of inclusion through: Talent, Education & Communication, Employee Groups and Celebration.
Based in Bengaluru, India this Data Engineer will work as part of an elite team alongside data engineers and data visualization engineers focused on maximizing value from data while working on high priority business opportunities across all functions and geographies. The Data Engineer will collaborate with line of business users, business analysts, data analysts and data scientists on models and algorithms to deliver analytics insights and use cases.
The Data Engineer will leverage analytical, visualization, and data engineering skills using data to solve problems, unlock opportunities and create new insights. They will identify, explore, acquire, and transform internal and external data sets. They will use storytelling with data to share insights and inspire data driven actions.
This role will require both creative and collaborative working with IT and the wider business. It will involve evangelizing effective data management practices and promoting better understanding of data and analytics. The Data Engineer will also be tasked with working with key business stakeholders, IT experts and subject-matter experts to plan and deliver optimal analytics and data science solutions.
Build quick data pipelines: The primary responsibility of data engineers is to build quick data pipelines that will provision data ready for analysis to be utilized for Data Science and Machine Learning. This includes internal enterprise data assets and external second- and third-party data. The engineer should be a creative problem solver able to identify new opportunities that can be rapidly prototyped and evaluated working closely with stakeholders.
Analyze data to unlock insights: Move beyond descriptive reporting and data engineering by helping stakeholders identify relevant insights and actions from data. Use ML techniques, regression, cluster analysis, time series, etc. to explore relationships and trends in response to stakeholder questions and business challenges.
Create visualizations and tell great stories with data: The Data Engineer must be able to communicate insights in a way that invites understanding and compels action across multiple levels of the organization.
Educate and train: The engineer should be curious and knowledgeable about new data initiatives and how to address them. This includes applying their data and/or domain understanding in addressing new requirements. They will also be responsible for proposing appropriate (and innovative) data ingestion, preparation, integration and operationalization techniques in optimally addressing these data requirements. The engineer will be required to train counterparts such as data scientists, data analysts, LOB users or any data consumers in these data pipelining and preparation techniques, which make it easier for them to integrate and consume the data they need for their own use cases.
Become a data and analytics evangelist: The engineer will be considered a blend of data and analytics “evangelist,” “data guru” and “fixer.” This role will promote the available data and analytics capabilities and expertise to business unit leaders and educate them in leveraging these capabilities in achieving their business goals.