C

Data Architect - Business Intelligence

Contentstack
NewPosted today

LOCATION

Bangalore · Hybrid

EXPERIENCE

8+ Years

SKILLS REQUIRED

Dimensional ModelingSnowflakeDBTData GovernanceSemantic ModelingData Quality

Job description

Overview

Senior BI Data Architect to lead the analytical modeling architecture and engineering standards that power reporting, semantic modeling, and AI-enabled analytics across the enterprise, using Snowflake and dbt.

What you'll do

  • Define and govern enterprise analytical architecture standards and scalable modeling frameworks across all layers (staging, intermediate, dimensional, fact, semantic, and mart layers), leveraging Snowflake and dbt.
  • Establish standards for model grain declaration, naming conventions, ownership metadata, lineage, and documentation.
  • Lead architectural design reviews for new modeling initiatives and analytical platform changes.
  • Partner with Data Engineering teams to align ingestion patterns and source system architecture with downstream analytical requirements.
  • Lead the design and technical implementation of governed business entities, semantic models, and enterprise metrics in partnership with BI and Analytics.
  • Design, implement, and enforce secure access patterns (APIs, RBAC, query design) for applications, AI agents, and self-service tools consuming Snowflake data through governed semantic models.
  • Translate complex business requirements from Revenue Operations, Finance, and executive leadership into scalable, trustworthy data models and BI solutions.
  • Establish and enforce scalable analytics engineering standards for dbt development, testing, deployment workflows, Git practices, CI/CD, model performance, observability, and deployment reliability.
  • Partner with BI Data Engineering teams to improve model consistency, modularity, scalability, and long-term maintainability.
  • Mentor analytics engineers on modular architecture, semantic implementation, reusable modeling patterns, and modern analytics engineering best practices.
  • Evaluate and recommend tooling, governance capabilities, semantic technologies, and platform improvements that support scalability and reduce technical debt.

What you'll need

  • 8+ years in data engineering, analytics engineering, or data architecture roles, with at least 3 years operating in a senior or lead architect capacity with direct analytical platform ownership.
  • Deep, hands-on expertise with Snowflake architecture, including virtual warehouse design, RBAC, materialization strategies, dynamic tables, and query performance optimization.
  • Expert-level dbt Labs practitioner with experience in staging/intermediate/mart conventions, Jinja macros, incremental strategies, testing frameworks, documentation, and reusable modeling patterns.
  • Demonstrated experience designing and deploying production semantic layers serving governed metrics across BI platforms, analytics applications, and AI-enabled analytics workflows, including text-to-SQL and MCP-based analytics integrations.
  • Strong command of dimensional and semantic modeling concepts, with the ability to select and justify the appropriate modeling approach based on business and analytical requirements.
  • Advanced SQL proficiency and experience with Python; familiarity with modern analytics tooling including dbt Cloud, Fivetran, Git/CI-CD workflows, and cloud-native analytics environments.
  • Experience designing secure access patterns for applications consuming Snowflake data, including APIs, service layers, RBAC, query performance, and governed semantic access.
  • Strong written and verbal communication skills with the ability to present architectural decisions to executive and cross-functional stakeholders.

Nice to have

  • dbt Certified Data Architect or Analytics Engineer certification.
  • Snowflake SnowPro Core or Advanced certification.
  • Snowflake Cortex and Snowpark ML experience for in-warehouse AI/ML workloads.
  • Experience with Salesforce as a source system, including GTM dimensional modeling from CRM objects.
  • RAG architecture experience connecting LLMs to governed analytical data foundations.
  • Experience working with BI tools such as Tableau, Looker, or Power BI.
  • Experience with data governance frameworks including data catalogs, column-level lineage, and row-level security.

Details

  • Location: Bangalore/Chennai
  • Work mode: Hybrid

Read the full description and apply on the company’s own careers page.

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Data Architect - Business Intelligence