What Are We Looking For?
We are seeking a BI Data Architect to lead the analytical modeling architecture and engineering standards that power reporting, semantic modeling, and AI-enabled analytics across the enterprise. In this high-impact role, you will establish scalable modeling patterns and reusable frameworks across Snowflake and dbt while partnering with leadership to operationalize governed metrics and long-term analytics strategy through architectural implementation best practices.
Key Responsibilities
- Architectural Leadership and Governance
- 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.
- Data Modeling and Semantic Layer
- Lead the design and technical implementation of governed business entities, semantic models, and enterprise metrics in partnership with BI andAnalytics.
- 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.
- Analytics Engineering and Platform Enablement
- 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.
Required Qualifications
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; dbt Certified Data Architect or Analytics Engineer certification preferred.
- 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.
- Snowflake SnowPro Core or Advanced certification strongly preferred.
Preferred Qualifications
- 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.
Experience: 10-15 years
Location: Bangalore/Chennai/Pune/Virar
What Do We Offer?
Interesting Work | We hire curious trendspotters and brave trendsetters. This is NOT your boring, routine, cushy, rest-and-vest corporate job. This is the “challenge yourself” role where you learn something new every day, never stop growing, and have fun while you’re doing it.
Tribe Vibe | We are more than colleagues, we are a tribe. We have a strict “no a**hole policy” and enforce it diligently. This means we spend time together - with spontaneous office happy hours, organized outings, and community volunteer opportunities. We are a diverse and distributed team, but we like to stay connected.
Bragging Rights | We are dreamers and dream makers. Our efforts pay off and we work with the most prestigious brands, from big-name retailers to airlines, to professional sports teams. Your contribution will make an impact with many of the most recognizable names in almost every industry including AirFrance KLM, ASICS, Burberry, Mattel, Mitsubishi, Walmart, and many more!
One Team One Dream | This is one of our values, and it shows. We don’t believe in artificial hierarchies. If you’re part of the tribe, you have an opportunity to contribute. Your voice will be heard and you will also receive regular updates about the business and its performance. Which, btw, is through the roof, so it’s a great time to be joining…
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