Data Modeler

Job Title: Data Modeler

Experience: 7–10 Years

Employment Type: Full-Time

Role Summary

We are seeking an experienced Data Modeler to support enterprise cloud data modernization and Oracle migration initiatives. The ideal candidate will have strong expertise in enterprise data modeling, Databricks Delta Lake, Lakehouse architectures, metadata management, and cloud data platforms, with proven experience migrating legacy Oracle workloads to modern cloud-native data platforms.

This role will be responsible for designing scalable conceptual, logical, and physical data models, enabling data governance, and supporting analytics and AI/ML-ready data products. The successful candidate will collaborate with Data Architects, Data Engineers, Business Analysts, and Analytics teams to build modern, secure, and high-performing enterprise data platforms.

Key Responsibilities

• Design, develop, and maintain conceptual, logical, and physical data models for enterprise data platforms.
• Define and implement scalable data models supporting:
• Data Warehousing
• Lakehouse Architectures
• Operational Data Stores
• Analytics and Business Intelligence
• AI/ML data products
• Lead data modeling activities for Oracle modernization and cloud migration initiatives.
• Analyze legacy Oracle data models and design optimized target-state models for cloud platforms.
• Support migration of Oracle workloads to:
• Databricks Delta Lake
• Snowflake
• Azure SQL Database
• Azure Synapse Analytics
• PostgreSQL
• MongoDB and other modern databases
• Design and implement data models leveraging Databricks Delta Lake and Lakebase capabilities.
• Develop and maintain enterprise metadata, reference data, and business glossaries.
• Implement data governance standards, metadata management, lineage, and cataloging practices.
• Collaborate with Data Engineers to support ETL/ELT pipeline development and data integration.
• Define data quality rules, validation standards, and governance controls.
• Support AI/ML initiatives by designing data models optimized for feature engineering and machine learning workloads.
• Optimize data structures for performance, scalability, and cloud-native architectures.
• Participate in architecture reviews, design workshops, and cloud modernization initiatives.
• Produce comprehensive data modeling documentation, standards, and technical specifications.
• Work closely with business stakeholders to translate business requirements into scalable enterprise data models.

Required QualificationsEducation

• Bachelor’s degree in Computer Science, Information Technology, Engineering, Data Science, or a related field.

Experience

• 7–10 years of experience in Data Modeling, Data Architecture, or Enterprise Data Management.
• Strong experience designing enterprise data models for cloud and analytics platforms.
• Experience supporting large-scale cloud migration and data modernization programs.
• Proven experience with Oracle database modernization initiatives.

Required Technical SkillsData Modeling

Strong expertise in:

• Conceptual Data Modeling
• Logical Data Modeling
• Physical Data Modeling
• Dimensional Modeling
• Star Schema
• Snowflake Schema
• Normalization and Denormalization
• Data Warehouse Modeling
• Lakehouse Modeling

Databricks & Lakehouse

Hands-on experience with:

• Databricks Delta Lake
• Databricks Unity Catalog
• Delta Sharing
• Databricks Lakebase
• Metadata Governance
• Lakehouse Architecture

Cloud Platforms

Experience with one or more cloud platforms:

• Microsoft Azure
• Amazon Web Services (AWS)
• Google Cloud Platform (GCP)

ETL/ELT & Data Integration

Experience with:

• Azure Data Factory (ADF)
• dbt
• Informatica
• Fivetran
• Other enterprise ETL/ELT tools

Database Technologies

Strong experience with:

• Oracle Database
• Snowflake
• Azure SQL Database
• Azure Synapse Analytics
• PostgreSQL
• MongoDB
• Other modern relational and NoSQL databases

Data Governance & Metadata Management

Experience with:

• Microsoft Purview
• Collibra
• Alation
• Informatica Enterprise Data Catalog (EDC)

Strong understanding of:

• Metadata Management
• Data Lineage
• Data Cataloging
• Master Data Management (MDM)
• Data Quality Frameworks
• Data Governance Best Practices

Preferred Qualifications

• Experience in Oracle-to-cloud migration projects.
• Experience designing AI/ML-ready data products and feature engineering datasets.
• Knowledge of Data Mesh, Data Fabric, or modern distributed data architectures.
• Experience working in highly regulated industries such as:
• Healthcare
• Financial Services
• Insurance
• Experience supporting enterprise analytics and business intelligence initiatives.
• Familiarity with Agile development methodologies and DevOps practices.
• Azure, Databricks, Snowflake, or cloud platform certifications are preferred.

Key Competencies

• Enterprise Data Modeling
• Data Architecture
• Databricks Delta Lake
• Lakehouse Design
• Oracle Modernization
• Cloud Data Migration
• Metadata Management
• Data Governance
• Master Data Management (MDM)
• Data Quality
• AI/ML Data Readiness
• SQL & Database Design
• Problem Solving
• Stakeholder Collaboration
• Technical Documentation

Why Join Us?

• Lead enterprise-scale cloud data modernization and Oracle migration initiatives.
• Work with cutting-edge technologies including Databricks Delta Lake, Unity Catalog, and Lakebase.
• Contribute to AI/ML-ready data platforms and modern Lakehouse architectures.
• Collaborate with cross-functional teams to build scalable, secure, and governed enterprise data solutions.

Work Location: Hybrid remote in Noida, Uttar Pradesh (Noida)