Architecting Scalable Data Models for Cloud Platforms

3 days ago

Pune, Maharashtra, India beBeeData Full time ₹ 15,00,000 - ₹ 25,00,000
Job Title: Enterprise Data Model Architect

Description:

As a seasoned data professional, we are seeking an accomplished Enterprise Data Model Architect to design and implement scalable and modular data models for our cloud-based platform. This role requires expertise in designing enterprise-level data models, incorporating region and country-specific extensions while ensuring global core integrity.

Key Responsibilities:

1. Design and implement data models that meet business requirements and ensure scalability, semantic consistency, and reusability.
2. Collaborate with cross-functional teams to embed business logic into models and translate functional requirements into technical architecture.
3. Develop and maintain documentation, metadata, and data lineage for all models.
4. Ensure adherence to data security, RBAC, and compliance best practices.
5. Optimize models for performance, data quality, and governance compliance.
6. Leverage tools like Matillion or equivalent ETL/ELT tools for model integration workflows.

Required Skills & Experience:

1. 5+ years of data modeling experience, with at least 3 years in a senior or lead role.
2. Proven expertise in designing enterprise-level data models for cloud data platforms, preferably Snowflake.
3. Strong understanding of data warehouse design patterns (dimensional, Data Vault, and other modeling approaches).
4. Ability to embed business logic into models and translate functional requirements into technical architecture.
5. Experience managing and approving changes to the core data model, ensuring scalability, semantic consistency, and reusability.
6. Proficiency in SQL with experience in Snowflake-specific features (streams, tasks, dynamic tables).
7. Familiarity with ELT/ETL tools such as Matillion, DBT, Talend, or Azure Data Factory.
8. Experience with DevOps practices, including Git/Bitbucket for version control of modeling artefacts.
9. Knowledge of metadata management, data lineage, and data cataloguing tools.
10. Strong understanding of data privacy, governance, and RBAC best practices.
11. Excellent communication and stakeholder engagement skills, including leading workshops.

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