Director, Data Architect

About Pivot Bio:
Fueled by an innovative drive and a deep understanding of microbiology, genomics, crop nutrition and agriculture, Pivot Bio is pioneering game-changing advances in fertilizer technology. Our first commercial product harnesses the power of naturally-occurring microbes, modern gene editing and application technologies to provide nitrogen to crops. We are dedicated to providing new solutions for farmers to improve yield as they work to help feed the world’s growing population.

Read/Hear more about Pivot Bio on Forbes or PBS News Hour.

Pivot Bio's Director, Data Architect will play a key role in making data actionable at all levels of the organization to inform decisions, actions, and strategy. 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 Director, 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.

• 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

• 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, Power
  
  BI)
• 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

• 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)
• Understanding of agronomic data, crop nutrition, soil science, or precision agriculture would be a strong plus
• Track…