Senior Data Product Manager, Agriculture

DTN is a global data and technology company helping operational leaders in agriculture, energy, and weather-driven industries make faster, smarter decisions. The Senior Data Product Manager, Agriculture will lead foundational agricultural data products, defining their strategy, governance, structure, and delivery across customer-facing products, analytics, APIs, and AI experiences. The role will drive cross-functional data initiatives, prioritize investments, and enable trusted, scalable data capabilities for agricultural customers.

Responsibilities:

• Own the strategy, roadmap, and investment priorities for agricultural data products, including pipelines, canonical data models, APIs, and shared data services
• Identify common data needs across DTN’s agriculture portfolio and translate them into scalable, reusable platform capabilities
• Prioritize investments based on customer value, commercial opportunity, data quality, technical feasibility, and long-term scalability
• Evaluate new datasets and capabilities for strategic fit, differentiation, commercialization potential, and their ability to enable analytics, machine learning, and AI use cases
• Partner with Data Engineering, Architecture, Data Science, and Product teams to translate customer and product needs into scalable data solutions
• Drive data initiatives from discovery and definition through delivery, adoption, and continuous improvement
• Define requirements for data quality, coverage, freshness, reliability, governance, and accessibility
• Drive alignment and resolve tradeoffs across complex data initiatives spanning multiple products, systems, and teams
• Define success metrics across data quality, reliability, adoption, operational efficiency, customer value, and commercial impact
• Use product performance, customer needs, and stakeholder feedback to continuously improve DTN’s data products
• Identify opportunities to expand how DTN’s agricultural data supports analytics, machine learning, predictive models, and AI
• Help establish the trusted data foundation required for DTN’s agricultural data to be reliably discovered, understood, and used by both people and AI systems

Requirements:

• 6+ years of Product Management experience, including ownership of complex data, platform, or B2B SaaS products
• Demonstrated experience leading products from strategy and discovery through delivery and ongoing optimization
• Strong product judgment and business acumen, with the ability to make effective decisions in technically complex and ambiguous environments
• Ability to balance customer value, commercial opportunity, technical complexity, and long-term platform strategy
• Experience managing data-intensive products involving data pipelines, APIs, integrations, analytics, or data platforms
• Strong understanding of modern data architectures, including data lakes and warehouses, ETL/ELT pipelines, APIs, cloud infrastructure, data modeling, and governance
• Experience partnering closely with Data Engineering, Architecture, and Data Science teams
• Ability to make complex technical concepts understandable to both technical and non-technical audiences
• Understanding of the data requirements for machine learning and AI applications, including data quality, metadata, context, governance, and reliable access
• Excellent communication and stakeholder management skills across technical, product, commercial, and executive audiences
• Demonstrated ability to influence strategy and drive alignment without direct authority
• Strong prioritization and execution skills across complex, cross-team initiatives
• Experience in agriculture, ag-tech, data platforms, market intelligence, geospatial technology, or another data-intensive industry
• Familiarity with agricultural data, including farm and field data, crop production, weather, markets, agronomy, or agricultural supply chains
• Experience building data products that support analytics, predictive models, machine learning, or AI
• Experience with geospatial data, predictive analytics, or AI-ready data infrastructure