Data Modeling Specialist

KOUD; São Paulo; Hybrid; BRL 150,000 - 250,000; Full time

Benefits offered by this job

Hybrid work

Job summary

KOUD is seeking a Data Modeling Specialist to drive enterprise data modeling, architecture, governance, and metadata management across Azure Synapse Analytics, Oracle, and Databricks environments. You will design, develop, and maintain conceptual, logical, and physical data models to support analytics, AI, and operational solutions.

The role focuses on translating business requirements into scalable data structures, building Bronze-Silver-Gold models, and collaborating with Data Engineering

Qualifications

• Bachelor's degree in a related field.
• Strong experience in data modeling, data architecture, or enterprise data management.
• Experience creating logical and physical data models for large-scale data platforms.
• Experience supporting data warehouse, database, and lakehouse environments.
• Experience with enterprise data governance and metadata management initiatives.
• Strong knowledge of conceptual, logical, and physical data modeling.
• Experience with dimensional modeling, including Star and Snowflake Schemas.
• Knowledge of 3NF, Data Vault Modeling, and Canonical Data Modeling.
• Strong experience with Azure Synapse Analytics.
• Strong experience with Databricks Lakehouse Platform.
• Strong experience with Oracle Database.
• Knowledge of data warehousing and lakehouse architectures.
• Knowledge of reference data management and Master Data Management concepts.
• Experience with data lineage, metadata management, data catalog solutions, data stewardship, and data quality management.
• Experience with business glossary development.
• Experience with source-to-target mapping and data transformation design.
• Knowledge of ETL/ELT processes and integration architecture.
• Strong knowledge of SQL and PL/SQL.
• Strong documentation, communication, stakeholder management, and problem-solving skills.
• Ability to collaborate with different technical teams and business stakeholders.
• Fluent English.

Responsibilities

• Design and maintain enterprise conceptual, logical, and physical data models.
• Develop dimensional, normalized, and hybrid data models supporting analytics and operational workloads.
• Translate business requirements into scalable and maintainable data structures.
• Create subject area models, canonical data models, and data domain structures.
• Ensure alignment of data models with enterprise architecture and business capabilities.
• Design dimensional and reporting models optimized for Azure Synapse dedicated and serverless environments.
• Define partitioning, distribution, and performance optimization strategies.
• Support data warehouse and lakehouse architectures.
• Design data structures supporting Databricks Lakehouse architectures.
• Design Bronze, Silver, and Gold layer data models.
• Support Delta Lake implementations and data product development.
• Collaborate with Data Engineering teams to optimize model performance and scalability.
• Design and maintain normalized operational data models in Oracle.
• Support transactional and analytical databases.
• Define indexing, partitioning, and performance optimization standards.
• Collaborate with database administrators to ensure efficient physical database implementations.
• Create and maintain source-to-target mapping documentation.
• Define transformation rules and business logic for data integration solutions.
• Support data migration, modernization, and cloud transformation initiatives.
• Work with Data Engineers to ensure accurate implementation of data models and mappings.
• Validate data integrity across inbound and outbound interfaces.
• Support enterprise data governance initiatives.
• Define and maintain business and technical metadata.
• Establish and document data standards and naming conventions.
• Support data stewardship activities and governance reviews.
• Ensure compliance with enterprise data management policies and regulatory requirements.
• Document end-to-end data lineage from source systems through consumption layers.
• Support the implementation of lineage management tools and processes.
• Partner with governance teams to improve data transparency and traceability.
• Define data quality rules, standards, and validation requirements.
• Assist in root-cause analysis of data quality issues.
• Partner with Business Analysts, Data Architects, Data Engineers, and Solution Architects.
• Participate in architecture reviews and solution design workshops.
• Provide guidance on data modeling best practices and standards.
• Mentor junior team members in data architecture and modeling disciplines.
• Promote data management and governance best practices across the organization.

Skills

Data modeling

Data architecture

Azure Synapse

Databricks

Oracle

SQL

PL/SQL

Data governance

Metadata management

Canonical data modeling

Data Vault

English fluency

Communication

Education

Bachelor's in CS/IS

Master's degree

Tools

Purview

ER/Studio

Erwin

Informatica

Collibra

Unity Catalog

Job description

Koud is looking for a Data Modeling Specialist to work with one of our clients.

The position focuses on enterprise data modeling, data architecture, data governance, metadata management, data lineage, and data integration across Azure Synapse Analytics, Oracle, and Databricks environments. The professional will be responsible for designing, developing, and maintaining conceptual, logical, and physical data models that support analytics, reporting, AI, and operational data solutions.

Responsibilities:

• Design and maintain enterprise conceptual, logical, and physical data models;
• Develop dimensional, normalized, and hybrid data models supporting analytics and operational workloads;
• Translate business requirements into scalable and maintainable data structures;
• Create subject area models, canonical data models, and data domain structures;
• Ensure alignment of data models with enterprise architecture and business capabilities;
• Design dimensional and reporting models optimized for Azure Synapse dedicated and serverless environments;
• Define partitioning, distribution, and performance optimization strategies;
• Support data warehouse and lakehouse architectures;
• Design data structures supporting Databricks Lakehouse architectures;
• Design Bronze, Silver, and Gold layer data models;
• Support Delta Lake implementations and data product development;
• Collaborate with Data Engineering teams to optimize model performance and scalability;
• Design and maintain normalized operational data models in Oracle;
• Support transactional and analytical databases;
• Define indexing, partitioning, and performance optimization standards;
• Collaborate with database administrators to ensure efficient physical database implementations;
• Create and maintain source-to-target mapping documentation;
• Define transformation rules and business logic for data integration solutions;
• Support data migration, modernization, and cloud transformation initiatives;
• Work with Data Engineers to ensure accurate implementation of data models and mappings;
• Validate data integrity across inbound and outbound interfaces;
• Support enterprise data governance initiatives;
• Define and maintain business and technical metadata;
• Establish and document data standards and naming conventions;
• Support data stewardship activities and governance reviews;
• Ensure compliance with enterprise data management policies and regulatory requirements;
• Document end-to-end data lineage from source systems through consumption layers;
• Support the implementation of lineage management tools and processes;
• Partner with governance teams to improve data transparency and traceability;
• Define data quality rules, standards, and validation requirements;
• Assist in root-cause analysis of data quality issues;
• Partner with Business Analysts, Data Architects, Data Engineers, and Solution Architects;
• Participate in architecture reviews and solution design workshops;
• Provide guidance on data modeling best practices and standards;
• Mentor junior team members in data architecture and modeling disciplines;
• Promote data management and governance best practices across the organization.

Requirements:

• Bachelor's degree in Computer Science, Information Systems, Data Management, Engineering, or a related field;
• Strong experience in data modeling, data architecture, or enterprise data management;
• Strong experience creating logical and physical data models for large-scale data platforms;
• Experience supporting data warehouse, database, and lakehouse environments;
• Experience with enterprise data governance and metadata management initiatives;
• Strong knowledge of conceptual, logical, and physical data modeling;
• Experience with dimensional modeling, including Star and Snowflake Schemas;
• Knowledge of Third Normal Form (3NF), Data Vault Modeling, and Canonical Data Modeling;
• Strong experience with Azure Synapse Analytics;
• Strong experience with Databricks Lakehouse Platform;
• Strong experience with Oracle Database;
• Knowledge of data warehousing, lakehouse architectures, and enterprise information architecture;
• Knowledge of reference data management and Master Data Management concepts;
• Experience with data lineage, metadata management, data catalog solutions, data stewardship, and data quality management;
• Experience with business glossary development;
• Experience with source-to-target mapping and data transformation design;
• Knowledge of ETL / ELT processes and integration architecture;
• Strong knowledge of SQL and PL/SQL;
• Strong documentation, communication, stakeholder management, and problem-solving skills;
• Ability to collaborate with different technical teams and business stakeholders;
• Fluent English.

Preferred:

• Master's degree;
• Experience with Microsoft Purview or similar metadata and governance tools;
• Experience supporting cloud modernization initiatives;
• Knowledge of Databricks Unity Catalog and governance capabilities;
• Understanding of AI, analytics, and machine learning data requirements;
• Experience within Insurance, Financial Services, or other regulated industries;
• Familiarity with DataOps and DevOps practices;
• Experience with SQL Server;
• Experience with Python;
• Experience with Erwin Data Modeler, ER/Studio, SAP PowerDesigner, Microsoft Purview, Collibra, or Informatica Metadata Manager.

Additional Information:

• Hybrid position, with 3 days per week working on-site in Pinheiros, São Paulo.