Manager, Enterprise Data Architecture (Hybrid)

 

Foods people love. Brands people trust. And a career that nourishes your future like no other.

 

If you're driven by the passion to do something meaningful that changes lives, Nestlé is the place for you. Nestlé USA is one of seven operating companies that make up Nestlé’s presence in the United States. We're in 97% of American homes, and as the leading food and beverage company, our goals are to continue to deliver quality food and beverage products, strengthen our local communities, and reduce our environmental and climate impact.

 

We’re determined to challenge the status quo and be better tomorrow than we are today. As individuals and teams, we embrace our entrepreneurial culture and have created a workplace where collaboration is essential, courage is rewarded, speed is expected, and agility is the norm to delight our consumers every single day. Here, you will find limitless opportunities to learn and advance your career and feel empowered to succeed in the workplace and beyond. Because our focus is not only on nourishing our customers, but also about enriching you.

 

This position is not eligible for Visa Sponsorship.

 

 

Digital Acceleration – The Organization You Will Be Part Of

We have established a central Enterprise Analytics team to drive a culture of data and analytics driven business decision-making, from the executive boardroom to the store shelf. To fulfil this vision, we are building advanced data, analytical and automation capabilities while also delivering improved cross-functional insights to help the enterprise make faster and better decisions to ultimately win in the marketplace.

 

Position Summary – Your Impact

You will apply a deep understanding of the data architecture and engineering practices for enabling datasets for consumption in a data lake environment. You will also be responsible for working with the relevant data product teams and IT partner teams to address the data architecture and infrastructure needs while ensuring excellence in data operations, as well as to research, assess and deploy new data architecture and data modeling capabilities.

 

Primary Responsibilities – What You’ll Do

• Lead development of the NUSA data architecture strategy including analytic data platform architecture and data engineering.  Collaborate with regional and global IT to understand and integrate with regional/global architecture strategy.  
• Deep technical mastery in cloud data platforms (Snowflake, Azure, AWS) and expertise across the data enablement technologies – for example SQL-DBM for modeling, Azure Data Lake, SQL, Synapse Serverless, Azure Analysis Services, Azure ML Ops, Azure Data Factory, Databricks.  Knowledge of AI capabilities (vector DB, grahp DB) and data governance capabilieis (Data Observability, Purview, Data Quality tools, etc).  Experience integrating data into business intelligence environments and data science environments.
• Lead the NUSA Data Architecture organization in partnership with data management leadership.  Establish organization performance goals and metrics (quality of model design) and manage a team of data architectures responsible for working with the functions to understand business requirements and develop the right data design. Grow the organization by developing and implementing strong technical competency development programs. 
• Collaborate with Data Management leadership and Data Product Managers to ensure they follow data architecture and modeling standards. Partner with Data Governance program and IT to ensure data assets are properly architected by design and in compliance with Data Governance and Stewardship requirements. Perform data architecture and data modeling design reviews in partnership with IT to ensure the models are scalable and secure.
• Partnership with operating company regional and with global IT architecture and technology capabilities and innovation.
• Maintain a repository of all data architecture standards, procedures and artifacts. Create, publish, and maintain the master version of data models in system of record. Auditing data assets regularly to maintain integrity of data models quality.
• Develop and lead multi-cloud platform strategy and execution leveraging Azure, Snowflake, Databricks, etc.
• Define and maint