Data Modeler - Enterprise Data Platforms

Job Description :

Role & Responsibilities :

- In this role, you will translate complex business requirements, data flows, and enterprise processes into scalable conceptual, logical, and physical data models across multiple domains such as Customer, Product, Finance, and Supply Chain. You will collaborate closely with Data Architects, Data Engineers, Governance teams, and Business Stakeholders to ensure high-quality, traceable, and analytics-ready data ecosystems.

Key Responsibilities :

- Design and maintain conceptual, logical, and physical data models aligned with enterprise architecture standards.

- Collaborate with business stakeholders, analysts, and SMEs to understand business processes, KPIs, data lifecycles, and requirements.

- Analyze customer, product, and operational value chains to define critical data entities, relationships, and dependencies.

- Build scalable physical data models optimized for performance, analytics, and cloud data environments.

- Develop semantic data models enabling business-friendly access through BI and analytics platforms.

- Define and enforce data standards, naming conventions, metadata definitions, lineage tracking, and governance practices.

- Work closely with data engineering teams to align data pipelines with enterprise data models.

- Manage model documentation, version control, change tracking, and model governance.

- Support enterprise data quality, governance, business glossary, and metadata management initiatives.

- Contribute to trusted, reusable, and standardized enterprise data assets across business domains.

Ideal Candidate Profile :

- 7-15 years of experience in Data Modeling / Enterprise Data Architecture with strong hands-on expertise in conceptual, logical, and physical data modeling.

- Strong experience with enterprise modeling tools such as Erwin, ER/Studio, PowerDesigner, SQLDBM, or similar platforms.

- Deep understanding of Dimensional Modeling (Kimball/Inmon), Normalization, Schema Design, and Modern Data Warehouse principles.

- Proven experience designing data models for modern cloud data platforms such as Snowflake, Databricks, Redshift, Dremio, or equivalent environments.

- Strong SQL expertise, schema design capabilities, and ability to validate implementations alongside engineering teams.

- Good understanding of data governance, metadata management, lineage, and business glossary frameworks.

- Exposure to ETL/Data Integration tools such as Informatica, DBT, Airflow, or similar frameworks is preferred.

- Understanding of Master Data Management (MDM) and reference data management concepts is a plus.

- Experience working with High-Tech / Manufacturing domains including customer, product, or supply chain datasets is desirable.

- Bachelors / Masters degree in Computer Science, Information Systems, or a related technical discipline.

Note :

- Candidates with more than 15 years of total experience will not be considered.