Data Governance & Quality Engineer

About the role

We are seeking an experienced Data Governance & Quality Engineer to play a key role in shaping Agilent's modern data management landscape. In this role, you will combine data governance, metadata management, and data quality expertise to ensure business-critical data assets are governed, discoverable, trusted, and ready to support operational, analytical, and AI-driven use cases. You will help establish and maintain governance processes for data assets within Microsoft Fabric and enterprise data catalog environments, while partnering with business stakeholders, data owners, architects, and analytics teams to improve the quality, usability, and transparency of commercial data. This role is ideal for a professional who enjoys working at the intersection of business processes, technology, and data governance and who wants to help build the foundation for the next generation of analytics and AI capabilities.

Responsibilities

• Govern critical data assets by defining and maintaining metadata, business definitions, ownership, stewardship responsibilities, classifications, quality requirements, and certification criteria.
• Manage enterprise data catalog content, business glossary entries, lineage documentation, and impact analysis to keep data assets discoverable, understandable, and trusted.
• Partner with data owners and subject matter experts to establish governance standards, accountability models, and processes for semantic models, governed data products, and enterprise reporting assets.
• Support Agilent's adoption of Microsoft Fabric, Power BI, Snowflake, and modern data management capabilities, with a focus on governed, reusable, and business-ready data assets.
• Use SQL, Snowflake, Power BI, and related tools to analyze data, validate governance controls, and support quality and metadata monitoring activities.
• Collaborate with Data Architecture, Data Engineering, and Analytics teams to embed governance, catalog, semantic layer, and monitoring requirements into solution design and delivery.
• Profile enterprise data to assess quality, identify risks, establish baselines, and define data quality rules, KPIs, and monitoring processes for critical business data.
• Perform root cause analysis and drive sustainable remediation of data quality issues in partnership with business and technical teams.
• Develop monitoring and scorecard solutions that provide visibility into data quality, governance performance, and commercial readiness.
• Act as a trusted advisor for system implementations, integrations, business process changes, and digital transformation initiatives where data governance and quality are critical to commercial readiness.
• Partner with stakeholders across Sales, Services, Marketing, and Operations to promote data literacy, stewardship, and practical governance best practices.

Qualifications

• Bachelor's or Master's degree in Computer Science, Information Management, Business Analytics, Engineering, Mathematics, Statistics, or a related field.
• 3+ years of experience in Data Governance, Metadata Management, Data Quality, Analytics, Business Intelligence, or related disciplines.
• Strong SQL skills and experience working with large enterprise datasets.
• Experience with Power BI, Snowflake, SAP, CRM, HANA, or similar enterprise platforms.
• Experience with data catalogs, metadata management, business glossaries, lineage, data ownership models, and stewardship frameworks.
• Understanding of semantic models, modern analytics architectures, and governed data products.
• Experience defining and implementing data quality standards, monitoring frameworks, and remediation processes.
• Familiarity with Microsoft Fabric or similar cloud-based analytics ecosystems.
• Ability to translate business requirements into practical governance and data management solutions.

Pay

The full-time equivalent pay range for this position is $124,160.00 - $194,000.00 per year plus eligibility for bonus, stock, and benefits. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.

Schedule

This is a full-time position with a standard weekly schedule and the option to work remotely.