Senior Analyst - Data & AI Governance

JOB DESCRIPTION Senior Analyst - Data & AI Governance The Big Picture Sysco LABS is the Global In-House Center of Sysco Corporation (NYSE: SYY), the world’s largest foodservice company. Sysco ranks 56th in the Fortune 500 list and is the global leader in the trillion-dollar foodservice industry. Sysco employs over 75,000 associates, has 337 smart distribution facilities worldwide, and over 14,000 IoT-enabled trucks serving 730,000 customer locations. For fiscal year 2025 that ended June 29, 2025, the company generated sales of more than $81.4 billion. Sysco LABS Sri Lanka delivers the technology that powers Sysco’s end-to-end operations. Everything we do at Sysco LABS supports Sysco’s Purpose of “Connecting the world to share food and care for one another” , and our work directly impacts millions of food consumers in a trillion-dollar, global industry. For more information visit: Job Summary Supports the organization's data governance program by executing day-to-day metadata management operations within the enterprise Data Catalog. Works directly with data owners, stewards, and domain stakeholders to ensure data assets are accurately described, classified, and assigned appropriate ownership. Partners with data stewards to define and implement data quality rules that improve the reliability and trustworthiness of critical data assets across the organization. Duties and Responsibilities: Execute Metadata Management Operations: Own and execute the end-to-end process of cataloging data assets in Alation (or comparable tool), including assuring completeness of asset descriptions, assigning data owners and stewards, and classification tags in alignment with established data governance standards and taxonomies. Support Data Quality Rule Development: Partner with data stewards and domain owners to identify relevant data quality dimensions—completeness, accuracy, consistency, timeliness—and help define, document, and configure corresponding data quality rules within governance tooling. Track rule violations and coordinate with stewards on resolution. Maintain Data Catalog Hygiene: Conduct ongoing audits of catalog entries to identify gaps, inconsistencies, and stale metadata. Prioritize and remediate issues in coordination with data owners and the Data & Records Management Engineer, who provides automated discovery to complement manual curation efforts. Collaborate Across Governance Operations: Serve as the operational hub between engineering automation and risk compliance. Surface metadata coverage gaps and data quality trends to the Data & AI Risk Analyst, whose compliance assessments depend on accurate catalog coverage and quality metrics as evidence of control effectiveness. Facilitate Stewardship Activities: Support data steward communities by preparing materials, tracking stewardship assignments, and ensuring accountability for metadata completeness targets across business domains. Help onboard new stewards by explaining catalog workflows and quality rule processes. Document Standards and Procedures: Develop and maintain documentation for metadata management workflows, business glossary standards, classification taxonomies, and data quality rule libraries to support consistency, scalability, and onboarding of future team members. Qualifications: Education Required: Bachelor's degree from an accredited institution in a relevant field such as Information Systems, Computer Science, Data Management, or Business Analytics. Experience Required: Three (3) to five (5) years of experience in data management, data governance, or analytics roles. Demonstrated experience working with enterprise data catalog tools—Alation strongly preferred; Collibra, Atlan, or similar are acceptable. Hands-on experience writing and optimizing SQL queries across relational or cloud-based data environments. Experience collaborating with business stakeholders to document data definitions, business rules, and data quality criteria. Technical Skills and Abilities: SQL Proficiency: Strong working knowledge of SQL for data exploration, profiling, and quality validation across enterprise data environments, including cloud platforms such as GCP BigQuery. Python (Preferred): Familiarity with Python for data profiling, automation of repetitive metadata tasks, or quality rule scripting is a meaningful plus. Data Catalog Tooling: Practical knowledge of catalog features including lineage visualization, business glossary management, stewardship workflows, and classification frameworks. Analytical Mindset: Ability to assess data quality metrics, identify root causes of data issues, and communicate findings clearly to both technical and non-technical audiences. Attention to Detail: Demonstrated precision in maintaining metadata records, documentation, and governance artifacts at scale. Benefits US dollar-linked compensation Performance-based annual bonus Recognition and rewards programs Agile Benefits – special allowances for Health, Wellness & Academic purposes Paid birthday leave Team engagement allowance Comprehensive health & life insurance cover (extendable to parents and in-laws) Overseas travel opportunities and client environment exposure Hybrid work arrangement