We are looking for an experienced Data Modeler to support the design and delivery of enterprise data models across business domains such as Finance, Sales, Retail, Supply Chain, Product, Customer, and Digital Commerce.

The role will focus on translating business requirements into high-quality conceptual, logical, physical, and semantic data models.

The Data

Modeler will work closely with Data Architects, Product Owners, Business Analysts, Data Engineers, BI developers, and business stakeholders to ensure that data structures are consistent, scalable, governed, and fit for analytical consumption.

The idóneo candidate has strong experience in enterprise data modeling, dimensional modeling, lakehouse or data warehouse environments, and modern analytics platforms such as Databricks or similar technologies. Key Responsibilities

Data Modeling Create and maintain conceptual, logical, and physical data models

Design entities, attributes, relationships, hierarchies, keys, and cardinalities.

Develop dimensional models, including facts, dimensions, bridge tables, slowly changing dimensions, and aggregation structures.

Define and document business entities such as Customer, Product, Store, Order, Transaction, Supplier, Account, and similar core business concepts.

Support the design of reusable and conformed data models across domains and data products. Semantic and Analytical Modeling Design models optimized for analytics, reporting, and BI consumption.

Define business metrics, measures, dimensions, hierarchies, and calculation logic.

Support semantic layer design for tools such as Power BI, Databricks SQL, Databricks Metric Views,



or similar platforms.

Ensure consistent business definitions for KPIs and analytical measures.

Collaborate with BI teams to ensure models are usable, performant, and understandable for reporting consumers. Source-to-Target Mapping Analyze source system structures and map them to target data models.

Create and maintain source-to-target mappings, including transformation logic and business rules.

Identify gaps, inconsistencies, duplicate structures, and data quality issues in source systems.

Work with Data Engineers to translate mappings into implementation-ready pipeline logic.

Support validation of implemented data models against business and technical requirements. Skills

Technical Skills

Strong knowledge of data modeling methodologies: Conceptual, logical, physical, dimensional

Strong SQL skills

Understanding of database and lakehouse concepts: tables, views, keys, constraints, partitioning, clustering, delta tables, schema evolution

Experience with cloud data platforms, ideally Databricks

Understanding of BI and semantic modeling concepts: Semantic layers, Metrics layers, DatabricksSQL, PowerBI Soft Skills:

Strong analytical thinking and attention to detail.

Ability to understand complex business processes and translate them into data structures.

Strong communication skills with both business and technical stakeholders.

Structured and documentation-oriented working style.

Ability to challenge unclear requirements and identify inconsistencies.

Collaborative mindset and willingness to work across teams.

Ability to work independently as an external consultant.

📌 Sr Data Modeler (Argentina)
🏢 Texplorers
📍 Argentina