{"id":2196952,"url":"https://alion.io/job/keep-simple-data-modeling-specialist","title":"Data Modeling Specialist","company":{"id":2593999,"name":"Keep Simple","domain":"keepsimple.io","url":"https://alion.io/company/keepsimple","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Gupy","truth_index":null},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["São Paulo, Brazil"],"countries":["BR"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":47000,"max_usd":120000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":2157},"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"Collibra","optional":false},{"name":"Data Vault","optional":false},{"name":"Databricks","optional":false},{"name":"Delta Lake","optional":false},{"name":"Dimensional Modeling","optional":false},{"name":"Erwin","optional":false},{"name":"ETL/ELT","optional":false},{"name":"Informatica","optional":false},{"name":"Master Data Management","optional":false},{"name":"Oracle","optional":false},{"name":"Python","optional":false},{"name":"Snowflake","optional":false},{"name":"SQL","optional":false},{"name":"Machine Learning","optional":true}],"status":"live","first_seen_at":"2026-10-09T18:08:34Z","employer_posted_date":"2026-10-09","last_verified_at":"2026-10-12T08:11:49Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"Come work for a large global financial and insurance products company! This is your chance !!\nStart a successful career in a renowned company in the international market! Great opportunity!\nGlobal insurance and asset management company seeks a responsible, organized, dynamic and team-oriented person.\nResponsabilidades e atribuições\nWe are seeking an experienced Data Modeling Specialist to design, develop, and maintain enterprise data models that support modern analytics, reporting, AI, and operational data solutions. This role will be responsible for creating and governing conceptual, logical, and physical data models across cloud and on-premise platforms, including Azure Synapse Analytics, Oracle, and Databricks.\nThe ideal candidate will possess deep expertise in data architecture, data modeling standards, metadata management, data lineage, and governance practices. The role will partner closely with Data Engineers, Solution Architects, Business Analysts, Governance teams, and Data Product Owners to ensure consistent, scalable, and business-aligned data designs.\nKey Responsibilities\nData Modeling:\nDesign and maintain enterprise conceptual, logical, and physical data models;\nDevelop dimensional, normalized, and hybrid data models supporting analytics and operational workloads;\nTranslate business requirements into scalable and maintainable data structures;\nCreate subject area models, canonical data models, and data domain structures;\nEnsure alignment of data models with enterprise architecture and business capabilities.\nPlatform-Specific Data Design\nAzure Synapse Analytics:\nDesign dimensional and reporting models optimized for Synapse dedicated and serverless environments.\nDefine partitioning, distribution, and performance optimization strategies.\nSupport data warehouse and lakehouse architectures.\nDatabricks:\nModel data structures supporting Lakehouse architectures;\nDesign Bronze, Silver, and Gold layer data models;\nSupport Delta Lake implementations and data product development;\nCollaborate with Data Engineering teams to optimize model performance and scalability.\nOracle:\nDesign and maintain normalized operational data models;\nSupport transactional and analytical databases;\nDefine indexing, partitioning, and performance optimization standards;\nCollaborate with database administrators to ensure efficient physical database implementations.\nData Mapping and Integration:\nCreate and maintain source-to-target mapping documentation;\nDefine transformation rules and business logic for data integration solutions;\nSupport data migration, modernization, and cloud transformation initiatives;\nWork with Data Engineers to ensure accurate implementation of data models and mappings;\nValidate data integrity across inbound and outbound interfaces.\nData Governance and Metadata Management:\nSupport enterprise data governance initiatives.\nDefine and maintain business and technical metadata.\nEstablish and document data standards and naming conventions.\nSupport data stewardship activities and governance reviews.\nEnsure compliance with enterprise data management policies and regulatory requirements.\nData Lineage and Data Quality:\nDocument end-to-end data lineage from source systems through consumption layers;\nSupport implementation of lineage management tools and processes;\nPartner with governance teams to improve data transparency and traceability;\nDefine data quality rules, standards, and validation requirements;\nAssist in root-cause analysis of data quality issues.\nCollaboration and Leadership:\nPartner with Business Analysts, Data Architects, Data Engineers, and Solution Architects;\nParticipate in architecture reviews and solution design workshops;\nProvide guidance on data modeling best practices and standards;\nMentor junior team members in data architecture and modeling disciplines;\nPromote data management and governance best practices across the organization.\nRequisitos e qualificações\nRequired Qualifications\nEducation:\nBachelor's degree in Computer Science, Information Systems, Data Management, Engineering, or a related field;\nMaster's degree preferred.\nExperience:\n7+ years of experience in data modeling, data architecture, or enterprise data management;\nProven experience creating logical and physical data models for large-scale data platforms;\nExperience supporting data warehouse, database, and lakehouse environments;\nExperience with enterprise data governance and metadata management initiatives.\n\nRequired Technical Skills\nData Modeling:\nConceptual Data Modeling;\nLogical Data Modeling;\nPhysical Data Modeling;\nDimensional Modeling (Star and Snowflake Schemas);\nThird Normal Form (3NF);\nData Vault Modeling;\nCanonical Data Modeling.\nData Platforms:\nAzure Synapse Analytics;\nDatabricks Lakehouse Platform;\nOracle Database;\nSQL Server (Preferred).\nData Architecture\nData Warehousing;\nLakehouse Architectures;\nEnterprise Information Architecture;\nReference Data Management;\nMaster Data Management Concepts.\nData Governance\nData Lineage;\nMetadata Management;\nData Catalog Solutions;\nData Stewardship;\nData Quality Management;\nBusiness Glossary Development.\nData Integration:\nSource-to-Target Mapping;\nData Transformation Design;\nETL / ELT Processes;\nIntegration Architecture.\nTools (Preferred):\nErwin Data Modeler;\nER/Studio;\nSAP PowerDesigner;\nMicrosoft Purview;\nCollibra;\nInformatica Metadata Manage.\nTechnical Languages\nSQL;\nPL/SQL;\nPython (Preferred).\nPreferred Qualifications:\nExperience with Microsoft Purview or similar metadata and governance tools;\nExperience supporting cloud modernization initiatives;\nKnowledge of Databricks Unity Catalog and governance capabilities;\nUnderstanding of AI, analytics, and machine learning data requirements;\nExperience within Insurance, Financial Services, or other regulated industries;\nFamiliarity with DataOps and DevOps practices.\nKey Competencies:\nEnterprise Data Architecture;\nData Modeling Expertise;\nBusiness Analysis;\nInformation Governance;\nAnalytical Thinking;\nDocumentation and Communication;\nStakeholder Management;\nProblem Solving;\nAttention to Detail;\nCollaboration and Leadership.\nSuccess Measures:\nHigh-quality, reusable, and scalable data models delivered across data platforms;\nAccurate and complete source-to-target mappings;\nComprehensive data lineage documentation;\nImproved data governance and metadata management maturity;\nIncreased consistency of enterprise data assets and standards;\nSuccessful support of analytics, reporting, AI, and regulatory reporting initiatives.\nInformações adicionais\nModelo de contratação:\nPJ.\nForma de atuação:\nHibrido (3x por semana presencial no escritório de Pinheiros/SP).","description_format":"text","description_chars":6634,"description_truncated":false,"requirements":{"experience_years_min":7,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":true},"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"Brazil","iso":"BR","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Personal Development","Coaching & Mentoring"],"lifecycle":[{"event":"open","at":"2026-10-09T19:51:18Z"}],"visa":[],"liveness":{"score":90,"band":"hot","label":"Hiring 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