Sr. Data Analytics Engineer with Sigma

Coforge is seeking a Sr. Data Analytics Engineer with Sigma to enhance their data analytics capabilities. The role involves designing data models, implementing AI functions, and building interactive workflows to improve data governance and operational efficiency.

Responsibilities:

• EArchitect Data Models : Design governed Sigma Data Models on top of Snowflake, translating raw database schemas into an intuitive, business-friendly semantic layer
• Centralize Logic & Security : Develop reusable core metrics and enforce inherited row-level security within the semantic layer, ensuring a single source of truth and strict data governance
• Deploy AI Capabilities : Leverage Sigma Assistant and Snowflake Cortex to enable secure, natural-language querying (NLQ) for business stakeholders
• Enrich Data Natively : Implement inline AI functions directly within workbooks to classify, summarize, and extract insights from unstructured text at warehouse scale
• Build Interactive Workflows : Transform static dashboards into dynamic operational applications using Sigma UI components for cross-functional tasks like forecasting and budget approvals
• Enable Scenario Modeling : Design robust workbooks leveraging dynamic parameters and Input Tables to support complex, human-in-the-loop "what-if" analysis
• Implement Secure Writeback : Configure Sigma Input Tables to push user inputs, manual adjustments, and workflow decisions directly back to dedicated Snowflake schemas
• Optimize & Audit : Maintain immutable audit trails for all writeback activity and balance live-query performance with strategic Snowflake materializations

Requirements:

• Advance SQL
• Sigma
• snowflake
• Dashboard
• 10+ years of experience
• Semantic Modeling & Governance
• Architect Data Models: Design governed Sigma Data Models on top of Snowflake, translating raw database schemas into an intuitive, business-friendly semantic layer
• Centralize Logic & Security: Develop reusable core metrics and enforce inherited row-level security within the semantic layer, ensuring a single source of truth and strict data governance
• AI Integration
• Deploy AI Capabilities: Leverage Sigma Assistant and Snowflake Cortex to enable secure, natural-language querying (NLQ) for business stakeholders
• Enrich Data Natively: Implement inline AI functions directly within workbooks to classify, summarize, and extract insights from unstructured text at warehouse scale
• Workflow Design & Operational Apps
• Build Interactive Workflows: Transform static dashboards into dynamic operational applications using Sigma UI components for cross-functional tasks like forecasting and budget approvals
• Enable Scenario Modeling: Design robust workbooks leveraging dynamic parameters and Input Tables to support complex, human-in-the-loop 'what-if' analysis
• Snowflake Writeback & Architecture
• Implement Secure Writeback: Configure Sigma Input Tables to push user inputs, manual adjustments, and workflow decisions directly back to dedicated Snowflake schemas
• Optimize & Audit: Maintain immutable audit trails for all writeback activity and balance live-query performance with strategic Snowflake materializations