Manager, Analytics Operations

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Information Technology







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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, and Club Monaco, among others, constitute one of the world's most widely recognized families of consumer brands.

Position Overview

The Manager, Analytics Operations is a new role in Ralph Lauren’s Analytics team, and will play a pivotal role building the most critical data and analytics initiatives for Ralph Lauren’s digital business initiatives. 

Purpose & Scope: 

Based in Bengaluru, India the Manager, Analytics Operations is a senior leader in the analytics organization accountable for the success and optimization of all production analytics and reporting processes.  This individual will lead a team of engineers managing all aspects of our production operations. The Director combines leadership skillsData/DevOps experience, data and technical expertise, and an operations mindset to provide the highest performing data assets to the organization.

Essential Duties & Responsibilities

  • Lead a Team of Engineers with a culture of continuous improvement to deliver the highest performance and availability from our data platforms.
  • Run & Optimize the Data Pipelines, Models, Databases, Cubes, Visualizations and other products developed by the Analytics, Enterprise Data, or Business Unit Data Teams.  Accountable for performance, availability, uptime, and cost.  Drive continuous improvement in cost and performance.
  • Run & Optimize the Platforms and tools used across the Analytics team including AWS Redshift, MicroStrategy, Airflow, AWS Elastic Map Reduce, AWS Kinesis, etc. Accountable for performance, availability, uptime and cost of the environment.  Accountable for the systems roadmap and platform upgrades. Drive continuous improvement in cost and performance.
  • Defines and Operates the Production Management Processes and Standards including accepting applications into production, code deployment, incident handling, and testing.  Sets standards to be followed by engineering and analytics teams on application design related to operations.
  • Accountable for Production SLAs.  Partners with Business and Analytics stakeholders to set SLAs, understand tradeoffs and cost implications.  Ensures that applications are tested to meet SLAs prior to production deployment.
  • Drives issue resolution including end user and system related incidents.  Build and staff a team capable of providing 24 x7 operations for a global team.  Ensure optimal performance during peak holiday selling seasons.

Experience, Skills & Knowledge

The ideal candidate will have a combination of IT skills, data governance skills, analytics skills and Retail industry knowledge with a technical or computer science degree.

Strong experience with DevOps/DataOps practices is required.

Strong experience in Lean Six Sigma and/or Agile development is preferred. 

Retail Industry knowledge or previous experience working in the business would be a plus.

Technical Knowledge/Skills

Deep technical expertise in big data, data warehousing, analytics, and data science related technologies including data lakes, ETL/ELT, data modeling, data visualization, and machine learning using AWS.

Strong experience with AWS cloud architecture

Strong experience using Python and/or R in an enterprise big data and advancement analytics environment.

Strong experience with relevant technologies including AWS Redshift and Spectrum, AWS Athena, AWS Kinesis, and MicroStrategy.

Strong experience in working with large, heterogeneous datasets in building and optimizing data pipelines, pipeline architectures and integrated datasets using traditional data integration technologies.

Experience in deploying and maintaining machine learning models and algorithms.

Strong experience in working with data governance, data quality, and data security teams and specifically and privacy and security officers in moving data pipelines into production with appropriate data quality, governance and security standards and certification.

Experienced in agile methodologies and capable of applying DevOps and increasingly DataOps principles to data pipelines to improve the communication, integration, reuse, and automation of data flows between data managers and consumers across an organization

Interpersonal Skills and Characteristics

Strong experience supporting and working with cross-functional teams in a dynamic business environment.

Required to have the ability to interface with, and gain the respect of, stakeholders at all levels and roles within the company.

Is a confident, energetic self-starter, with strong interpersonal skills.

Has good judgment, a sense of urgency and has demonstrated commitment to high standards of ethics, regulatory compliance, customer service and business integrity.