Technical Architect, Dairy Predictive Solutions

Zoetis•US MI Remote, MI

1d•$140,000 - $210,000•Onsite

About The Position

Leads the design and evolution of the overarching technical architecture for the Dairy Predictive Solutions platform, ensuring seamless integration across the front-end customer experience, data infrastructure, R&D algorithmic development, and enterprise systems. Serves as the primary technical visionary responsible for defining how phenotypic data ingestion pipelines, predictive algorithm frameworks, and customer-facing applications connect and scale to support growing numbers of customers and expanding global footprint. Orchestrates architectural decisions across cross-functional teams including internal business leaders, data scientists, software engineers, product designers, and external stakeholders including producers, veterinarians, and customers to inform technical, operational, and design requirements. Must be able to work with business stakeholders (internal and external) to review and refine requirements including the development of prototypes, architectural proofs of concept, and reference architectures outside production environments. Holds primary accountability for ensuring the platform architecture supports compliance with established protocols, data governance standards, and scalability requirements. Leverages expertise in dairy production software systems and associated data elements, modern cloud architecture, and strategies related to the use of data-driven insights on-farm to inform the architecture of dairy data ecosystems and the development and delivery thereof. The successful candidate is a systems thinker who can balance strategic, long-term architectural vision with near-term delivery priorities in a dynamic, rapidly evolving environment.

Requirements

Bachelor's degree in Computer Science, Information Systems, Software Engineering, Data Science, or related field.
7+ years of experience in data architecture, software architecture, or systems engineering roles, with demonstrated experience designing scalable, production-grade platforms.
3+ years of experience working with advanced analytics, predictive models, or data science teams in a product delivery context.
5+ years of experience with cloud-based data platforms (e.g., Databricks, AWS, Azure, GCP), data lakes, data warehouses, and modern data engineering patterns.
Deep expertise in cloud architecture and services (AWS, Azure, or GCP) required.
Strong experience with data engineering tools and platforms including Databricks, Spark, or equivalent (required).
5+ years of experience with relational SQL databases, data modeling, and query optimization (required).
Experience with API design, microservices architecture, and system integration patterns (required).
Proficiency in Python and/or other programming/scripting languages (required).
Experience with AI-supported development (required).

Nice To Haves

Master's degree or advanced degree preferred.
Experience in dairy production, agriculture technology, or related life sciences industries is strongly preferred.
Proven ability to define and communicate architectural vision to both technical and non-technical audiences.
Strong communication and stakeholder management skills with the ability to work across time zones in support of global business units.
Experience with CI/CD pipelines, infrastructure-as-code, and DevOps practices (preferred).
Experience with dairy or livestock software platforms including DC305, Bovisync, PCDart, or DHIPlus and understanding of underlying data elements is preferred.
Familiarity with front-end technologies and user experience architecture is a plus.
Experience with machine learning deployment pipelines (MLOps) is preferred.
Strategic, systems-level thinker with the ability to translate business and scientific objectives into robust technical architectures.
Customer-obsessed mindset with empathy for dairy producer challenges and workflows.
Comfort with ambiguity and ability to drive clarity in complex, cross-functional problem spaces.
Collaborative leader who can influence without authority across engineering, data science, product, and business teams.
Passion for leveraging technology to improve animal health outcomes.
Entrepreneurial spirit with initiative to identify and pursue architectural opportunities that unlock product and business value.
Demonstrated commitment to achieving objectives in a manner supportive of Zoetis values.

Responsibilities

Define and own the end-to-end technical architecture for the Predictive Dairy Solutions platform, encompassing data ingestion, storage, algorithmic processing, API layers, and front-end delivery.
Ensure all architectural components are designed for scalability, reliability, and performance as the platform grows in customer count and geographic reach.
Design the data infrastructure architecture for phenotypic data ingestion, transformation, and storage, ensuring it can support the volume, variety, and velocity of data required by R&D algorithm development and commercial product delivery.
Architect the integration layer that connects the front-end customer experience, backend data systems, R&D initiatives, and third-party platforms (e.g., herd management systems, laboratory systems), enabling seamless data flow and a cohesive product experience.
Partner with R&D and data science teams to design infrastructure that empowers rapid development, testing, and deployment of dairy predictive algorithms and models, bridging the gap between scientific innovation and production-grade systems.
Develop scalability and globalization strategies for the platform architecture, including multi-region deployment patterns, data residency considerations, and performance optimization to support international expansion.
Prepare and maintain comprehensive architectural documentation, including system design specifications, data flow diagrams, integration blueprints, and technical roadmaps for business and technical stakeholders.
Evaluate emerging technologies and architectural patterns to continuously improve the platform's capabilities, performance, and cost efficiency.
Provide technical guidance and mentorship to development teams on architectural best practices.