Company Description QZENSYS is a trusted professional services partner providing IT staffing, consulting, software development, and technology solutions across modern platforms and tools. The company focuses on helping organizations build agile, future-ready teams by supplying specialized talent and expertise in cutting-edge technologies.

QZENSYS emphasizes quality, reliability, and client success, supporting digital transformation initiatives and competitive growth in a rapidly changing technology landscape. In addition to staffing and consulting, QZENSYS delivers end-to-end software development services across diverse technology stacks and platforms, offering comprehensive support to its clients.

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We are looking for an experienced Data Modeler responsible for designing scalable, governed, and high-performance data models for enterprise data platforms. The role will work closely with Data Architects, Data Engineers, BI developers, business stakeholders, and application teams to translate business requirements into logical and physical data models.

The candidate should have solid experience in enterprise data modeling, dimensional modeling, data warehousing, cloud data platforms, and modern Lakehouse architectures

Key Responsibilities

Design for enterprise data platforms.

Conceptual, Logical and Physical Data Models

Develop dimensional models using Star and Snowflake schemas.

fact and dimension tables

Design , including conformed dimensions.

Define .

grain, keys, relationships, cardinality and referential integrity

SCD Type 1, Type 2 and other historical tracking approaches

Design .

Work with Data Architects to define enterprise data architecture and modeling standards.





Create models for environments.

Data Warehouse, Data Lake and Lakehouse

Develop data models for Bronze, Silver and Gold layers in a Lakehouse architecture.

Optimize models for analytical workloads and BI reporting.

Work closely with Power BI/Tableau teams to create models suitable for semantic-layer consumption.

Analyze source systems and map source attributes to target data models.

Perform and define transformation rules.

source-to-target mapping

Identify data quality, duplication, normalization and data integrity issues.

Define metadata, business definitions and data lineage.

Support .

Data Governance, Master Data Management and reference-data modeling

Collaborate with Data Engineers during implementation and validate the implemented model.

Review SQL queries and database structures for performance and scalability.

EXPERTISE AND QUALIFICATIONS

Core Data Modeling

Conceptual, Logical & Physical Data ModelingER Modeling

Relational Data Modeling

Dimensional Modeling

Star/Snowflake Schema

Fact & Dimension Design

SCD Type 1 / Type 2

Normalization / Denormalization

Data Vault — good to have

Enterprise Data Modeling

Canonical Data Models

Master & Reference Data Modeling

Data Warehousing

Enterprise Data Warehouse

Data Marts

ETL/ELT architecture

Source-to-Target Mapping

Data Integration

Data Quality

Data Lineage

Cloud / Modern Data Platforms

Databricks / Delta Lake

Unity Catalog

Lakehouse Architecture

Azure Data Lake Storage

Azure Synapse

AWS Redshift

Snowflake — good to have

Microsoft Fabric — good to have

Modeling Tools

Experience with one or more:

ER/Studio

Erwin Data Modeler

Sparx Enterprise Architect

SAP PowerDesigner

SQL Developer Data Modeler dbt

Databricks data-modeling capabilities

📌 Data Modeler | Warehousing 6 to 8+ yrs exp (Pune)
🏢 Qzensys Solutions
📍 Pune