Description

Key Skills: AWS, Azure Databricks, SQL, Data modeling, Snowflake, Data Modelling, Data Model, Data Governance, Python, Metadata

Roles and Responsibilities:

• Design and maintain conceptual, logical, and physical data models for enterprise analytics, reporting, and AI/ML workloads.
• Develop dimensional, relational, and hybrid models (e.g., star, snowflake, and data vault where applicable) aligned to BI consumption patterns.
• Optimize data models for Snowflake performance, scalability, and cost efficiency.
• Collaborate with data engineering teams to implement models in Databricks (Spark) environments and ensure correct source-to-target mappings.
• Support AI/ML and GenAI feature and data model readiness, including lineage, traceability, and reuse of data assets.

Skills Required:

• 5 - 10 years of experience in data modeling, data architecture, or analytics engineering.
• Data modeling concepts (conceptual, logical, physical) and strong expertise in data model design.
• SQL proficiency for building and validating data models and transformations.
• Hands-on experience with Snowflake data modeling and performance optimization.
• Cloud data architecture experience on Azure and/or AWS, including Azure Databricks and analytics workloads.

Good to Have:

• Data governance experience, including metadata and lineage standards.
• Python familiarity for data modeling and validation workflows.

Education: Degree in Computer Science, Engineering, or a related field

Key Skills

Education

Any Graduate