C

Contentstack

Composable DXP with headless CMS

BI Data Architect - Business Intelligence

Data EngineeringConfirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaNo salary listed

About the Job

Requirements

  • At least 8 years of experience in data engineering, analytics engineering, or data architecture, including at least 3 years operating in a senior or lead architect capacity with direct analytical platform ownership.
  • Hands-on expertise with Snowflake architecture, including virtual warehouse design, role-based access control, materialization strategies, dynamic tables, and query performance optimization.
  • Expert dbt Labs practitioner experience with staging, intermediate, and mart conventions; Jinja macros; incremental strategies; testing frameworks; documentation; and reusable modeling patterns.
  • Experience designing and deploying production semantic layers that serve 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 and ability to select and justify modeling approaches based on business and analytical requirements.
  • Advanced SQL proficiency and experience with Python; familiarity with modern analytics tooling including dbt Cloud, Fivetran, Git and CI/CD workflows, and cloud-native analytics environments.
  • Experience designing secure access patterns for applications consuming Snowflake data, including APIs, service layers, role-based access control, query performance, and governed semantic access.
  • Strong written and verbal communication skills and ability to present architectural decisions to executive and cross-functional stakeholders.

Responsibilities

  • Define and govern enterprise analytical architecture standards and scalable modeling frameworks across staging, intermediate, dimensional, fact, semantic, and mart layers using 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, including APIs, role-based access control, and 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.

Desired Qualifications

  • dbt Certified Data Architect or Analytics Engineer certification.
  • Snowflake SnowPro Core or Advanced certification.
  • Experience with Snowflake Cortex and Snowpark ML for in-warehouse AI/ML workloads.
  • Experience with Salesforce as a source system, including go-to-market dimensional modeling from CRM objects.
  • RAG architecture experience connecting large language models 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.

About the Company

Contentstack

Composable DXP with headless CMS

Contentstack is a digital experience platform (DXP) that helps businesses deliver personalized content across channels using a headless CMS. It stores content in a back-end repository and serves it via RESTful APIs to display on any device, enabling teams to publish and develop faster. The platform is composable, meaning it can be assembled from modular components, and it includes a built-in Marketplace, App SDK, and Developer Hub for customization. This setup differentiates Contentstack from competitors by offering a user-friendly onboarding (under 30 minutes), a strong ecosystem for extensions and integrations, and measurable gains in publishing velocity (up to 90%) and developer velocity (up to 80%). Revenue comes from a subscription model. The company's goal is to help organizations deliver consistent, personalized, omnichannel experiences while reducing costs and increasing business value.

Company size
501-1,000
Company stage
Series C
Total funding
$169M
Headquarters
Austin, TX
Founded
2018

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