Hybrid São Paulo: Enterprise Data Modeling Lead

KOUD

United States

Hybrid

USD 36,000 - 60,000

Full time

5 days ago

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Job summary

KOUD is seeking a Data Modeling Specialist to work with one of our clients on enterprise data modeling, governance, lineage, and data integration across Azure Synapse Analytics, Oracle, and Databricks. The role involves designing, developing, and maintaining conceptual, logical, and physical data models that support analytics, AI, and operational data solutions.

The position requires strong experience in data modeling, data architecture, and metadata management, with a focus on scalable data

Qualifications

Bachelor's degree in CS, IS, Data Management, Engineering, or 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 with data governance and metadata management initiatives.
Strong knowledge of conceptual, logical, and physical data modeling.
Experience with dimensional modeling (Star and Snowflake Schemas).
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.
Experience with data lineage, metadata management, data catalog solutions, data stewardship, and data quality management.
Fluent English.

Responsibilities

Design and maintain enterprise conceptual, logical, and physical data models.
Develop dimensional, normalized, and hybrid data models for 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 for Azure Synapse 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 Engineers to optimize model performance and scalability.
Design and maintain normalized operational data models in Oracle.
Define indexing, partitioning, and performance optimization standards.
Collaborate with DBAs for efficient physical 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 metadata.
Establish naming conventions and data standards.
Support data stewardship and governance reviews.
Ensure compliance with data management policies and regulatory requirements.
Document end-to-end data lineage from source systems through consumption layers.
Support 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 BAs, 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.