Sr Data Governance Architect

Bayer•Tulsa, OK

3d•$124,000 - $180,000•Remote

About The Position

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. As a Senior Data Governance Architect, you will develop and maintain data architecture across multiple data types for the organization to enable knowledge worker productivity, improve customer experience and business decision making with accurate, timely, and consistent information. In this role, you will work with architects, innovation managers, digital leads, data engineers and data scientists and many other profiles as well as external service providers to ensure that new capabilities comply with the information architecture. You will also be responsible for balancing the need for access against security, scalability, and performance requirements.

Requirements

Minimum Bachelor’s Degree in Engineering, Computer Science, Information Systems or related field and relevant professional experience
Background in supply chain, manufacturing or industrial operation in highly secure data environment
Specific knowledge of Google Big Query, Data Historian and Denodo/Data Virtualization
QA experience within software or data development contexts
Data architecture using SQL, Python, R, SAS, or other common languages
Strong expertise in data governance, including policy enforcement, data quality standards, validation rules, lineage documentation, and relational data modeling across complex, multi‑source environments.
Hands‑on experience with ETL/ELT pipelines and deployment processes, supporting scalable, well‑managed data infrastructure across environments.
Demonstrated strong oral and written communication, persuasiveness, and ability to communicate complex analytical approaches to all levels of business
Demonstrated innovative solutions and self-lead discoveries of new technologies
History of meeting tight deadlines and providing accurate estimates of time required to complete complex tasks

Nice To Haves

10+ years of experience with 3-5+ years experience in data engineering, data architecture, or data governance

Responsibilities

Design and implement regional data governance, lineage, and quality assurance frameworks to ensure accurate, reliable, and compliant product supply data pipelines.
Design and drive implementation of end-to-end data governance strategies, validation frameworks, and data quality tracking systems across supply chain operations
Assist in the technical execution of enforcing data standards, lineage documentation, and relational integrity policies across warehousing and visualization assets
Implement and maintain QA processes across data pipelines to ensure accuracy, completeness, and reliability of production data
Contribute to scalable data architecture and build high‑quality datasets and reporting solutions that meet cross‑functional engineering and business needs.
Contribute to the design and development of data systems and architecture across a range of organizational initiatives, informing how data infrastructure is structured and scaled
Build and deploy datasets tailored to user requirements for visualization and reporting across multiple platforms, with strong emphasis on quality and relational integrity
Designs and governs data foundations that enable responsible, ethical and scalable use of artificial intelligence(AI), including generative and advanced analytics use cases.
Drive the development of reporting solutions and collaborate with engineers and stakeholders to define data reporting needs, gather requirements, and investigate gaps in existing solutions
Architect and support deployment and environment foundations to ensure consistent, production‑ready data platforms.
Build and maintain a solid deployment infrastructure supporting the team's development and release workflows
Support CI/CD processes, deployment pipelines, and environment management across development and production systems
Translate complex data concepts into clear communication while partnering cross‑functionally to identify data optimization opportunities that improve operational efficiency and value.
Communicate architecture standards for data quality and data governance.
Communicate complex data concepts and project status clearly to both technical and non-technical audiences
Work cross-functionally to identify data optimization opportunities that improve workflow efficiency and deliver value to operations across the region