Data Steward

TP; Lisboa; Presencial; EUR 42 000 - 56 000; Tempo integral

Resumo da oferta

TP is seeking a data governance professional to join a collaborative team responsible for implementing and operating an enterprise data governance framework. You will help improve data trust, usability, compliance, and accountability across the organization by ensuring critical data assets are properly defined, owned, cataloged, classified, and monitored for quality.

In this role you will define ownership, stewardship, business terms, data definitions, and usage rules; maintain the data catalog

Responsabilidades

• Support the definition and maintenance of data ownership, stewardship responsibilities, business terms, data definitions, and usage rules across assigned domains
• Maintain and enrich the enterprise data catalog and business glossary, ensuring metadata, classifications, lineage, and ownership information remain accurate and up to date
• Collaborate with data owners, business stakeholders, analysts, architects, and data engineers to define data quality expectations, business rules, validation criteria, and remediation processes
• Monitor data quality issues, support root-cause analysis, track remediation actions, and escalations across data domains

Descrição da oferta de emprego

Join a collaborative team supporting the implementation and ongoing operation of an enterprise data governance framework. In this role, you’ll help improve data trust, usability, compliance, and accountability across the organization by ensuring critical data assets are properly defined, owned, cataloged, classified, and monitored for quality.

What you'll do

• Support the definition and maintenance of data ownership, stewardship responsibilities, business terms, data definitions, and usage rules across assigned domains;
• Maintain and enrich the enterprise data catalog and business glossary, ensuring metadata, classifications, lineage, and ownership information remain accurate and up to date;
• Collaborate with data owners, business stakeholders, analysts, architects, and data engineers to define data quality expectations, business rules, validation criteria, and remediation processes;
• Monitor data quality issues, support root-cause analysis, track remediation actions, and escalat... etc.