Sr Data Governance Architect

Tasks and 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.
• Aid 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.
• Design and govern 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.

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.
• 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-led discoveries of new technologies.
• Demonstrated history of meeting tight deadlines and providing accurate estimates of time required to complete complex tasks.

Qualifications

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

Skills

• Data architecture using SQL, Python, R, SAS, or other common languages.

Benefits

Employees can expect to be paid a salary of approximately $124k-180k. Additional compensation may include a bonus or incentive program (if relevant).

Additional benefits include health care, vision, dental, retirement, PTO, sick leave, etc.