Senior Business Analytics, Data Engineer

Company Description
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.

Position Overview
As a Senior Data Engineer specializing in pipeline optimization, you will play a crucial role in improving the performance, scalability, and reliability of our existing data pipelines. In this senior-level position, you will lead efforts to analyze, identify bottlenecks, and implement solutions to optimize data processing workflows. You will collaborate closely with cross-functional teams, mentor junior engineers, and provide technical expertise to drive pipeline optimization initiatives.

Essential Duties & Responsibilities
1. Lead the analysis and assessment of existing data pipelines to identify performance bottlenecks, scalability limitations, and areas for improvement. 2. Collaborate with data engineers, SME's, Functional Team Members, and stakeholders to understand data requirements, business objectives, and user needs. 3. Lead the design and implement strategies to optimize data ingestion, transformation, and storage processes, ensuring efficient and reliable data flow. 4. Collaborate with infrastructure teams to optimize resource allocation, infrastructure configuration, and system performance. 5. Mentor and provide technical guidance to junior data engineers, promoting best practices for pipeline optimization and data engineering methodologies. 6. Collaborate with stakeholders to understand emerging business requirements and propose innovative solutions to meet evolving needs. 7. Document pipeline modifications, configurations, and troubleshooting procedures to ensure knowledge sharing and continuity.

Experience, Skills & Knowledge
1. Bachelor's degree in Computer Science, Engineering, or a related field. A master's degree is a plus. 2. Extensive experience working as a Data Engineer, focusing on optimizing data pipelines. 3. Strong programming skills in languages such as Python, and SQL. 4. In-depth knowledge of big data technologies like Hadoop, Spark, or similar distributed computing frameworks. 5. Solid understanding of data modeling, data warehousing, and ETL principles. 6. Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform. 7. Proficiency in data visualization tools and techniques for monitoring pipeline performance. 8. Strong analytical and problem-solving skills with the ability to troubleshoot complex data pipeline issues. 9. Expertise in database systems and SQL for data retrieval and manipulation. 10. Excellent communication and collaboration skills to work effectively with cross-functional teams. 11. Ability to lead and drive pipeline optimization projects independently while managing multiple priorities.