Job Description

Whole Foods Market is seeking a Principal Solution Architect on Store Support Marketing Enterprise Analytics team in Austin. This team member will design, maintain and support the implementation of technical architectures to facilitate the achievement of WFM’s strategic business and technical goals. They will spread awareness around technology options and provide education to our Technology teams and our business. They will also act as a focal point for recommendations around technology direction, both short and long term. This team member will translate business strategy and requirements into a consolidated view that drives company-wide organizational, process, and technology changes. They will develop and lead the implementation of technology standards and ensures governance of those standards. They will define framework for the technical platforms, system specifications, input/output, and working parameters for hardware and/or software compatibility.

The AWS Solutions Architect will lead the architectural design and implementation of advanced pricing and promotions optimization algorithms in our tech ecosystem. They will be responsible for designing scalable solutions on AWS, integrating machine learning models, and collaborating with cross-functional teams. This role requires a deep understanding of both software engineering and data science, with a focus on delivering optimal pricing and promotion recommendations.

Responsibilities:

Solution Design and Architecture:

• Collaborate with stakeholders to understand technical requirements related to the optimization of pricing and promotions.
• Design scalable and robust architecture leveraging AWS services for machine learning and data processing.
• Incorporate customer-centric design principles into software development and optimization processes.

AWS Cloud Integration:

• Architect solutions on AWS cloud platform, recommending appropriate use of services such as SageMaker, S3, Redshift, Glue, and any other relevant tools.
• Ensure scalability, reliability, and cost effectiveness of the AWS infrastructure supporting our ML applications.

Data Management and Integration:

• Design data pipelines for ingesting, transforming, and managing large volumes of structured and unstructured data from diverse sources.
• Propose ETL processes and collaborate with tech teams to ensure data quality and consistency.

Technical Leadership and Collaboration:

• Provide guidance and mentorship to cross-functional teams including data scientists, analysts, and engineers
• Collaborate with product managers, business stakeholders, and tech teams to align technical solutions with business goals.
• Design software modules for data science components that are scalable, maintainable, and robust.
• Oversee the integration of the pricing and promotion optimization algorithms within existing systems and platforms.

Performance Optimization and Testing:

• Optimize algorithms and models for performance, scalability, and cost-effectiveness.
• Implement best practices for testing and quality assurance.
• Conduct rigorous monitoring and validation to ensure accuracy and reliability of ML models and software applications.

Documentation and Training:

• Document high-level and detailed architecture designs, technical specifications, and implementation plans.
• Provide training and support to end-users and technical staff on the use and maintenance of the software solution.

Proof of Concept and Prototyping:

• Lead proof of concept initiatives to evaluate new technologies and methodologies.
• Develop prototypes and pilot projects to demonstrate feasibility and potential business impact.

Cross-Functional Collaboration:

• Collaborate with tech teams to ensure seamless deployment and operation of ML models in production environments.

Thought Leadership and Continuous Improvement:

• Stay informed about emerging trends and advancements in machine learning, cloud computing, and retail technology.
• Continuously evaluate and propose enhancements to existing systems and processes to improve efficiency and effectiveness.

Change Management and Adoption:

• Drive change management initiatives to facilitate the adoption of new technologies and processes related to pricing and promotions optimization.
• Provide training and support to internal teams on the use and benefits of ML-driven solutions in retail operations.

Education and Qualifications:

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field.
• Proven experience as a Solutions Architect or similar role designing and implementing complex, scalable data science solutions.
• Hands-on experience with AWS cloud services and machine learning platforms. AWS Solutions Architect certification preferred.
• Strong proficiency in Python or similar programming languages for data analysis and model development.
• Solid understanding of software development lifecycle (SDLC) and agile methodologies.
• Excellent communication skills with the ability to convey complex technical concepts to non-technical stakeholders.

At Whole Foods Market, we provide a fair and equal employment opportunity for all Team Members and candidates regardless of race, color, religion, national origin, gender, pregnancy, sexual orientation, gender identity/expression, age, marital status, disability, or any other legally protected characteristic. Whole Foods Market hires and promotes individuals solely based on qualifications for the position to be filled and business needs.

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