Data Steward; Business Analytics & AI Readiness

At Bayer we’re visionaries, driven to solve the world’s toughest challenges and striving for a world where 'Health for all Hunger for none’ is no longer a dream, but a real possibility. We’re doing it with energy, curiosity and sheer dedication, always learning from unique perspectives of those around us, expanding our thinking, growing our capabilities and redefining ‘impossible’. There are so many reasons to join us.

If you’re hungry to build a varied and meaningful career in a community of brilliant and diverse minds to make a real difference, there’s only one choice.

Bayer Digital Farming Solutions (DFS) is seeking a Data Steward to partner and collaborate across Business Analytics, Data Engineering, Product Teams, and Data Governance to improve the quality, consistency, and usability of critical business data assets. The Data Steward will serve as a bridge between business and technical teams, helping establish data standards, business context, metadata, and quality processes that support analytics, operational reporting, and AI initiatives.

This role relies heavily on building strong relationships and working cross-functionally to promote data ownership, improve data quality, and ensure business stakeholders can confidently discover, understand, and use data. The successful candidate will play a key role in supporting data governance objectives, data migrations, metadata management, and AI readiness efforts across DFS. This position is ideal for someone passionate about data quality, governance, analytics, and enabling trusted data-driven decision making.

• Develop strong, collaborative relationships with business stakeholders, data owners, product teams, and technical partners to understand data challenges and drive stewardship initiatives.
• Serve as a liaison between Business Analytics, Data Engineering, Product, and Governance teams to align on data definitions, standards, and business requirements.
• Establish and maintain business metadata, including business terms, critical data elements, business rules, and data documentation.
• Identify, prioritize, track, and coordinate remediation of data quality issues across critical business datasets.
• Support data migration and modernization efforts by documenting data requirements, quality expectations, lineage, and business context.
• Monitor data quality trends and partner with stakeholders to improve completeness, accuracy, consistency, and reliability of data assets.
• Facilitate root cause analysis of recurring data issues and drive sustainable corrective actions.
• Partner with technical teams to ensure data warehouse, reporting, and AI-use-case requirements are reflected in data models and source systems.
• Support metadata management, data catalog, and governance tools by maintaining business context and stewardship information.
• Drive identification and governance of Critical Data Elements (CDEs) and other high-value business data assets.
• Develop and communicate data standards, stewardship practices, and business guidance to stakeholders.
• Promote AI readiness by ensuring key datasets are well-documented, governed, and accompanied by meaningful business context and metadata.
• Act as a steward for trusted data by improving discoverability, usability, and understanding of enterprise data assets.
• Support governance committees and working groups through preparation of materials, issue tracking, and stewardship recommendations.

Required:

• Bachelor's degree in Business, Information Systems, Data Analytics, Computer Science, or a related field, with 5-7 years of experience in data governance, business analytics, data management, business operations, or a related discipline.
• E…