SVP, Enterprise Data Analytics and Technology

About

At Macy's, Inc. we're on a mission to create a brighter future with bold representation for all. This is our Mission Every One. We know that each person here is unique. So, we respect and invest in each individual to create growth, pride, and satisfaction. If we are able to bring our whole selves to work, it translates into a more abundant and wider array of ideas and energy for all to benefit from. Our success will be built on amazing colleagues, working together.

Job Overview

The SVP, Enterprise Data and Analytics Technology shapes and implements the company’s data and analytics vision, collaborating closely with C-Suite Leadership and senior executives from both business and technology sectors. The focus is on fostering a data-driven culture throughout the organization where data is viewed as a strategic asset that generates business value. This leader actively leads, defines, and deploys top-tier data science and advanced analytics capabilities in support of Macy’s business ambitions. They design and develop supporting technologies for scalability and reusability.

This leader oversees a diverse team of experts, including data scientists, data engineers, Artificial Intelligence/Machine Learning specialists, business analysts, and data governance professionals. They leverage the unique strengths of each team member to establish standards for governance, engineering, architecture, AI, reporting, and analytics across Macy’s Inc. Having a deep understanding of Macy’s business processes and data utilization, this leader introduces modern data engineering and analytics techniques, emphasizing Data Ops & MLOps. They stay actively engaged in emerging data-related trends within the tech community. Additionally, they manage and develop their team, attracting top talent. With a proven track record, they develop and execute a comprehensive data strategy aligned with the company’s goals and objectives, gaining support across all organizational levels.

The Enterprise Data and Analytics Technology Leader at Macy’s Inc. reports to the Chief Information Officer. The position is based in Atlanta, GA.

What you will do: 

• Develop and drive the vision for data, analytics, and Artificial Intelligence / Machine Learning within Macy’s. Serve as a thought partner for the business and enable the use of data as a strategic asset to unlock business ambitions and value. 

• Define enterprise roadmap for managing data as an asset and a utility, unified data formats, and strategy to continuously streamline data landscape with end users in mind.

• Lead advanced analytics, business intelligence (BI), and reporting efforts to enable data-driven business decision making and process automation.

• Collaborate with key business leaders to understand, prioritize, and deliver the data platforms and tools they need based on key use cases in digital, commercial, operations, people, and finance.

• Define, manage, and advance enterprise information management principles, policies, and programs for stewardship, advocacy, and custodianship of data and analytics, in concert with legal, information security, and corporate risk and compliance offices.

• Build strong relationships, credibility, and trust with C-Suite and key business stakeholders to ultimately strengthen the data team’s credibility within the organization.

• Operate as a change agent to accelerate the journey of being a best-in-class data-driven organization. 

• Act as a steward of data literacy throughout the organization. 

• Organize and chair a Data & Analytics Data Governance organization, ultimately helping to establish and manage the governance of data and algorithms used for analysis, analytical applications, and automated decision making.

• Define and deploy data science and analytics best practices, including guidelines for tailoring analytics methodologies to specific business needs.

• Foster the creation of a data-driven culture and related competencies and data literacy across the enterprise with a focus on promoting data self-service.

• Develop and maintain controls on data quality, interoperability, and data sources to effectively manage the corporate risk associated with the use of data and analytics.

• Institute processes and data governance to ensure data pulled from various sources meets quality standards, is curated, and enhanced for analytical use, driving towards a "single source of truth".

• Oversee development and management of data infrastructure (e.g., data lake) for improved data accessibility.

• Stay abreast of emerging technologies and practices including but not limited to AI, Machine Learning, 

• Cloud, Advanced Analytics, and Business Intelligence Software.

• Foster a community of practice for all data, analytics and technology tea