Data & Analytics Domain Architect

Overview

With data deeply embedded in our DNA, PepsiCo Data, Analytics, and AI (D&AI) transforms data into consumer delight. We build and organize business-ready data and AI allowing PepsiCo's leaders to solve problems with the highest degree of confidence. Our data, analytics, AI products and services ensure our digital transformation is delivered at scale enabling new revenue streams, deeper partner relationships, new consumer experiences, and innovation across the enterprise.

As part of the Global Data & AI Architecture team, Architects are responsible for making PepsiCo's strategic vision real by defining the right architecture for conceiving, initiating, and shepherding high-priority data, analytics, and AI enabling capabilities.

• Defines Data & Analytics north star architecture (Data & Analytics capabilities and how they relate) and tech strategy (leads tech evaluation and selection, including POCs) and secures alignment across the following stakeholders: Global Data Governance, Data Engineering, Data Platform, Enterprise Solutions, and Digital Products and Applications team.
• Continues to refine data architecture principles and design patterns
• Perform regular and thorough market research, both with our existing product vendors, 3rd party research agencies like Gartner, and prospective vendors to stay one step ahead of the latest trends in the Data space. Evolve technology strategy and north star architecture accordingly.
• Lead the Data Architecture Community of Practice, providing coaching and guidance to D&AI solution architects, Enterprise Architects, and program teams on the use of Data capabilities, principles, and patterns along with documenting and presenting data architecture exceptions.
• Govern D&AI products solution architectures to ensure alignment with Data architecture standards and minimize tech debt, maximize reuse and speed to market

• The expected compensation range for this position is between $125,900 - $249,900.
• Location, confirmed job-related skills, experience, and education will be considered in setting actual starting salary. Your recruiter can share more about the specific salary range during the hiring process.
• Bonus based on performance and eligibility target payout is 25% of annual salary paid out annually.
• and an additional target payout of 10% of annual salary is paid out over 3 years following the end of the performance period.
• Long term incentive equity may be awarded based on eligibility and performance.
• Paid time off subject to eligibility, including paid parental leave, vacation, sick, and bereavement.
• In addition to salary, PepsiCo offers a comprehensive benefits package to support our employees and their families, subject to elections and eligibility: Medical, Dental, Vision, Disability, Health, and Dependent Care Reimbursement Accounts, Employee Assistance Program (EAP), Insurance (Accident, Group Legal, Life), Defined Contribution Retirement Plan.

• 10+ years of Data Lake / Warehouse hands-on Data Engineering Delivery
• Bachelor's Degree required; master's degree preferred
• Consulting experience building data, analytics and AI strategies for clients strongly preferred
• Experience working in large, multinational, enterprises
• Experience with large enterprise transformations
• Experience in CPG industry preferred
• Experience driving technology evaluations across a wide range of vendors using a formal evaluation process.

• Expert knowledge of key Data platforms such as Microsoft Azure (Fabric), Databricks and Snowflake.
• Expert knowledge in Data strategies and in delivering Data solutions for complex large enterprises
• Deep understanding of data architecture principles and industry best practices.
• Expert knowledge of key Data & Analytics platforms/technologies such as Azure Data Lake, Azure Data Factory, Informatica Cloud (Data Quality, Master Data Management), DataBricks, Azure ML, PowerBI, Tableau, Synapse.
• Exposure and understanding of existing digital and emerging technologies (AI including Gen AI and how it can improve Data & Analytics, Data Integration)
• Experience with data techniques and best practices on architecting data solutions for AI applications.
• Systems thinking, understanding of relationships between various systems
• Thorough understanding of the architecture guiding principles / modern architecture and leveraging them to design forward-looking solutions.
• Ability to demonstrate a mindset for the Conceptual, Logical, Physical levels of architecture and apply them effectively.
• Familiarity with information management practices, system development life cycle management, IT services management, infrastructure and operations, and EA frameworks
• Ability to influence senior stakeholders on following technology strategy and solution design for key initiatives to align with standards and architecture guiding principles

• Demonstrate interest in continuous self-learning and willingness to apply outside in thinking.
• Constantly adaptable to an ever-changing set of priorities.
• Master at the art of influencing to drive alignment at all levels of the organization, from development teams on usage of design patterns to Sr. VPs on tech strategy and solution rationalization.
• Excellent collaboration skills, also at all levels of the organization.
• Certification in data management or architecture.
• Executive level written, verbal, communication and presentation skills.
• Ability to turn complex things and diverse data into meaningful insights/conclusions and executive messaging
• Apply proper level of thoroughness and due diligence to architecture recommendations
• Familiarity with data science concepts and techniques is a plus.