Job Summary
We are seeking an experienced and detail-orientedData Stewardto drive the execution of enterprise data governance and data quality initiatives.
This role operates as anindependent contributor , responsible for ensuring that data assets are trusted, well-governed, and accessible across the organization.The Data Steward willown the governance, lineage, and quality of data assets across the full data lifecycle—from ERP source systems through RAW, consumable, and KPI layers.
Leveragingdata.worldas the enterprise data catalog, this role will ensure strong metadata management, lineage transparency, and data discoverability.A key focus of this role is toestablish a consistent, trusted semantic layer that supports analytics and AI use cases , ensuring data is clearly defined, standardized, and ready for downstream consumption.
The role requires a balance of governance expertise andhands-on technical capability (SQL and Python)to validate data, enforce quality, and support metadata and lineage automation.Preferred ExperienceHands-on experience withdata.worldor similar modern data catalog platforms.Strong understanding ofdata governance frameworks(e.g., DAMA-DMBOK).
Experience managingdata lineage and quality across multi-layered architectures(ERP, data lakes, transformation layers, KPI/reporting).




Experience supporting or buildingsemantic layers for BI and/or AI use cases.Proficiency inSQL and Python for data analysis, profiling, and automation of data quality checks.Experience working withAPIs or programmatic interfacesfor metadata and catalog automation.Familiarity withmodern data platforms(Databricks, Redshift, Athena).
Experience withdata visualization tools(e.g., Power BI).
Knowledge ofdata privacy and regulatory standards(e.g., GDPR, CCPA).
QualificationsBachelor's degree in computer science, Information Systems, Data Science, or related field.3+ years of experience indata stewardship, data governance, or data quality roles.Demonstrated experience working withdata catalogs, metadata management, and lineage.Strong problem-solving skills with the ability towork independently and manage moderately complex data challenges.Excellent communication and stakeholder management skills, with the ability toinfluence and drive adoption of governance practices.Comfortable workinghands-on with data using SQL and Pythonto validate data, enforce quality rules, and support governance processes.What Success Looks LikeTrusted, well-documented data assets acrossERP → KPI pipelineHigh adoption and effective use ofdata.worldConsistent and governedbusiness definitions and semantic layerMeasurable improvements indata quality KPIsReliable,AI-ready datasetssupporting analytics and decision-making

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