Ref #:
W145877
Department:
Data Analytics
City:
Bangalore
State/Province:
Karnataka
Country:
India
Pay Range Max

Pay Range Min

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

We are seeking an experienced Analytics Data Engineering Operations Manager/Sr Manager to lead our data engineering operations team, consisting of both internal and external resources. This individual will be responsible for overseeing the maintenance, optimization, and governance of our analytics data landscape. The ideal candidate will possess strong leadership skills, deep technical expertise in data engineering, and a proven track record of managing operations for complex analytics organizations.
Essential Duties & Responsibilities


Team Leadership:
Lead and manage a diverse team of data engineers, analysts, including both internal employees and external contractors or vendors.
Provide guidance, mentorship, and support to all team members to ensure high performance, collaboration, and professional development.
Foster a culture of accountability, innovation, continuous improvement & customer focus within the team.


Resource Management:
Oversee the allocation and utilization of internal and external resources to ensure efficient project execution and delivery.
Collaborate with internal stakeholders and external partners to define project requirements, timelines, and resource needs.
Manage relationships with external vendors or contractors, ensuring adherence to service level agreements (SLAs) and contractual obligations.


Incident and Problem Management:
Develop, implement & enhance processes for incident detection, response, resolution, and escalation.
Lead root cause analysis efforts to identify underlying issues and implement preventive measures to minimize future incidents.


Infrastructure Management:
Monitor system performance, troubleshoot issues, and implement solutions to ensure the stability, availability, and security of the data platform.
Ensure the availability, reliability, and scalability of systems to meet business needs and service level agreements (SLAs)


Quality Assurance and Governance:
Establish and enforce data quality standards, data governance policies, and compliance requirements across internal and external data engineering teams.
Implement monitoring and testing procedures to ensure data accuracy, consistency, and integrity, collaborating with both internal and external stakeholders.
Address data quality issues and drive continuous improvement initiatives, leveraging the expertise of internal and external resources.


Project Management:
Plan, prioritize, and manage projects, ensuring effective utilization of internal and external resources to achieve project goals and deliverables.
Collaborate with business teams and IT teams to manage change ensuring a seamless change process


Vendor Management:
Manage relationships with third-party vendors and service providers, including negotiating contracts, monitoring performance, and resolving issues.
Evaluate vendor products and services to ensure they meet business requirements and deliver value.
Experience, Skills & Knowledge

• Strong proficiency in data engineering tools and technologies, including but not limited to data warehouses, ETL processes, and data governance frameworks.
• Hands-on experience with cloud platforms (preferably AWS) and big data technologies (e.g., Databricks, Spark, Hive etc).
• Strong knowledge and experience of ITIL framework and best practices for IT service management
• Excellent leadership and communication skills, with the ability to effectively manage internal and external stakeholders and drive consensus on important decisions.
• Strong analytical and problem-solving skills, with a keen attention to detail and a commitment to delivering high-quality solutions.
• Experience in project management methodologies (e.g., Agile, Scrum) and tools (e.g., JIRA, Confluence) is a plus.
• Relevant certifications (e.g., AWS, SAFE, ITIL) are highly desirable.