{"id":3702164,"url":"https://alion.io/job/nov-data-governance-specialist","title":"Data Governance Specialist","company":{"id":1814757,"name":"NOV","domain":"nov.com","url":"https://alion.io/company/nov-com","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"A","score":85,"open_postings":76,"ghost_share":0,"stale_share":0.566,"repost_share":0.026,"time_to_fill_p50_days":40,"computed_at":"2026-11-09T06:03:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":null,"employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Rio de Janeiro, Brazil"],"countries":["BR"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Machine Learning","optional":false},{"name":"ETL/ELT","optional":true},{"name":"GDPR","optional":true},{"name":"ISO 27001","optional":true},{"name":"Oracle ERP","optional":true},{"name":"SQL","optional":true}],"status":"live","first_seen_at":"2026-11-03T18:33:26Z","employer_posted_date":"2026-11-03","last_verified_at":"2026-11-09T06:25:03Z","board_verified":true,"closed_at":null,"days_open":5,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":5},"description":"Working closely with business areas, Enterprise Architecture, Software and Architecture, Enterprise Systems and Process Performance, cybersecurity, corporate data teams, system owners and software vendors, the Data Governance Specialist will support the development, implementation and continuous improvement of SPS’s Data Governance Framework. The role will help establish and maintain data ownership, standards, definitions, metadata, data quality and access principles; support governance of KPIs and authoritative data sources; assess data requirements and reporting continuity throughout system implementation, replacement and decommissioning; and facilitate cross-functional governance activities to ensure that SPS data remains trusted, secure, accessible, traceable and fit for operational, analytical and decision-making purposes.\n Document SPS data domains, systems, sources, processes, information flows and data lineage.\nSupport the development and maintenance of the data catalog, business glossary and data dictionary.\nDefine and promote standards for data ownership, metadata, classification, access, retention and lifecycle management.\nEstablish data quality requirements, rules, monitoring practices and issue-management processes.\nSupport data integration, migration, reporting, analytics and data-product initiatives.\nAssess data impacts related to system implementations, integrations, migrations and decommissioning.\nHelp reduce dependency on uncontrolled spreadsheets and manually maintained datasets.\nPromote secure, traceable and responsible access to data.\nPrepare SPS data for artificial intelligence, machine learning and advanced analytics initiatives.\nFacilitate collaboration between business and technical stakeholders and promote data literacy across SPS\n Required education\nDegree in Computer Science, Computer Engineering, Software Engineering, Systems Engineering, Information Systems or a related field.\nEngineering, Administration or other relevant degrees may be considered when combined with appropriate experience in data, technology, systems or business processes.\nDesirable education\nBackground in Data Science, Statistics, Information Management, Business Analytics, Information Technology or related areas.\nPostgraduate education or certifications in data governance, data management, data engineering, data architecture, business intelligence, cybersecurity, privacy or digital transformation is desirable.\nRequired training/knowledge\nExperience in data governance, data engineering, data architecture, business intelligence or related disciplines.\nKnowledge of data modeling, relational databases, SQL, APIs, ETL/ELT, data integration, metadata, data quality and data lineage.\nEnglish proficiency is mandatory due to interaction with corporate teams, global stakeholders and software vendors.\nDesirable training/knowledge\nCloud data platforms, data warehouses, data lakes or lakehouse architectures.\nInformation security, privacy, access control and data lifecycle management.\nExperience with digital transformation, system implementation, migration or decommissioning projects.\nKnowledge of DAMA-DMBOK, COBIT, ISO 27001, ISO 38505 or comparable practices is desirable.\nKnowledge of GDPR (EU) and LGPD (BR) practices.\nKnowledge of Oracle ERP database 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