Lead Data Architect

Pivot Bio•Minneapolis, MN

7h•Onsite

About The Position

Pivot Bio's Lead Data Architect will play a key role in making data actionable at all levels of the organization to inform decisions, actions, and strategy. This individual will design and implement the company's data platform strategy creating the foundational architecture that connects lab discovery to field performance to manufacturing operations. The Data Architect works at the intersection of agronomic science, industrial operations, and commercial execution, designing modern, scalable data systems that organize and analyze data across all domains. In this role, the Lead Data Architect will develop and deliver long-term strategic goals for data architecture vision and standards in collaboration with cross-functional stakeholders. A critical aspect of the role is translating business requirements from Product Innovation, Manufacturing, and Commercial teams into elegant technical architectures that balance immediate needs with long-term scalability. This role will provide technical recommendations throughout the solution/data architecture and implementation lifecycle, working hands-on when needed to prove concepts and establish patterns. The Lead Data Architect reports to the Head of Digital and works in close partnership with Product, Engineering, and Data Science teams, interfacing with business stakeholders across R&D, Manufacturing, Agronomy, and Commercial functions. Strong candidates have deep data platform expertise, pragmatic architectural judgment, and the ability to translate complex scientific and business requirements into clean, scalable data systems. This role can be located in St. Louis, MO or Minneapolis, MN and will be onsite 4 days a week.

Requirements

Bachelor's degree in Computer Science, Engineering, or related field
10+ years of focused experience on data architecture and data engineering
Proven experience in enterprise data modeling including dimensional modeling, normalization strategies and domain-driven design
Deep hands-on experience with modern data platforms (Databricks strongly preferred)
Strong programming skills in SQL; proficiency with scripting languages (Python, R, similar)
Must be authorized to work in the United States
Data platform mastery: Expert in data lakes, warehouses, and data mesh architectures with deep Databricks experience
Data modeling expertise: Dimensional modeling, normalized schemas, graph databases, and domain-driven design
Modern data stack: Databricks (preferred), ETL/ELT tools, streaming technologies, and BI platforms (Tableau, PowerBI)
Data governance: Quality, profiling, security, metadata management, MDM, archival, and migration strategies
Technical depth: Advanced SQL, Python/scripting, query optimization, and performance tuning
Systems thinking: Balances strategic vision with pragmatic execution and speed-to-value trade-offs
Ambiguity navigation: Defines elegant architecture despite incomplete requirements or evolving business needs

Nice To Haves

Understanding of agronomic data, crop nutrition, soil science, or precision agriculture would be a strong plus
Track record designing data architectures that enable advanced analytics and AI/ML applications

Responsibilities

Define data architecture vision and standards in collaboration with stakeholders
Design and implement modern data platform integrating Lab, Manufacturing, Agronomic, and Corporate Operations across the agricultural value chain
Design integration patterns for 3rd party data sources including soil tests, machinery data, imagery, and partner APIs
Establish data governance framework including MDM policies, data quality standards, and security protocols
Enable AI-ready infrastructure supporting advanced analytics, ML models, and GenAI applications
Own data quality and availability across modeling, enrichment, and accessibility for all stakeholders
Validate architectures hands-on through POCs, implementation reviews, and technical problem-solving