Director, Analytics Technology Architecture
Ralph Lauren
Bangalore, Karnataka, India
4d ago

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

The Director, Analytics Technology Architecture 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 Director, Analytics Technology Architecture will define the technology and data architecture for analytics at Ralph Lauren.

This individual will lead a team of architects, engineers, and data governance leads in the use of data and technology to deliver our Connected Retail, Digital, Value Chain, and Financial objectives.

This individual is a thought leader driving our technology architecture, a subject matter expert on existing and emerging practices and tools, and an inspirational leader able to drive continuous advancement of our capabilities.

Essential Duties & Responsibilities

Define the technology architecture for analytics : Own the reference architecture and roadmap for data warehousing, analytics, and data science.

Provide solution architecture and design expertise and set relevant standards. Continuously evaluate the suitability of our analytics technology environment including tools, frameworks, and processes to satisfy our current and future business needs.

Understand the technology landscape in the broader retail industry and propose advancements to our roadmap.

Deliver enterprise platforms and tools for analytics : Deliver the environments, platforms, and tools for development of our enterprise data platforms, to support the advanced analytics and data science teams, and used by analytics teams embedded in business units.

Ensure uptime and performance meet business needs. Drive continuous improvement in cost and performance. Set standards for administrators and engineers.

Drive data governance for analytics : Define and operate our data governance processes and standards to ensure consistent, high quality data is available and agreed upon across the organization.

Define clear system of record and data lineage, deliver data catalog and metadata management solutions. Define standards for development teams to follow to publish and reuse high quality data assets.

Provide solution architecture expertise for projects and analytics groups as needed, acting as a subject matter expert and ensuring alignment to overall architecture goals.

Collaborate across departments : Leverage strong collaboration skills to partner with varied stakeholders within the organization, including the analytics and enterprise data warehouse teams, business stakeholders, security, infrastructure, and other teams.

Act as an evangelist for architecture and data governance best practices within IT and the business.

Experience, Skills & Knowledge

Education and Experience

  • A bachelor's or master's degree in computer science, statistics, applied mathematics, data management, information systems, information science or a related quantitative field is required.
  • An advanced degree in computer science (MS), statistics, applied mathematics (Ph.D.), information science (MIS), data management, information systems, information science (postgraduation diploma or related) or a related quantitative field is preferred.
  • 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.
  • Work experience in data and analyticsdisciplines including at least 6 years in a leadership position.
  • DeepRetail Industry knowledge or previous experience working in the business would be a plus.
  • TechnicalKnowledge / 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 using Python and / or R in an enterprise big data and advancement analytics environment.
  • Strong experience with relevant database technologies includingAWS Redshift and Spectrum, AWS Athena, AWS Aurora, Snowflake, SQL Server and similar platforms.
  • Strong experience in working with large, heterogeneous datasets in building and optimizing data pipelines, pipeline architectures and integrated datasets using traditional data integration technologies.
  • These should include ETL / ELT, data replication / CDC, message-oriented data movement and upcoming data ingestion and integration technologies such as stream data integration and data virtualization.

  • Strong experience in working with both open-source and commercial message queuing technologies such as Kafka, Amazon Simple queuing Service, stream data integration technologies such as Apache Nifi, Apache Kafka Streams, Amazon Kinesisand stream analytics technologies such as Apache Kafka KSQL.
  • Strong experience working with popular data discovery, analytics and BI software tools like MicroStrategy, Tableau, Qlik, PowerBI and othersfor semantic-layer-based data discovery.
  • Strong experience in working with data science teams in refining and optimizing data science and 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.
  • Demonstrated ability to work across multiple deployment environments including cloud, on-premises and hybrid, multiple operating systems and through containerization techniques such as Docker, Kubernetes, AWS Elastic Container Service and others.
  • 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 be highly creative and collaborative. An ideal candidate would be expected to collaborate with both the business and IT teams to define the business problem, refine the requirements, and design and develop data deliverables accordingly.
  • The successful candidate will also be required to have regular discussions with data consumers on optimally refining the data pipelines developed in nonproduction environments and deploying them in production.

  • 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
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