What Are We Looking For?
We’re looking for a Business Intelligence Data Architect to shape the analytical architecture, data modeling standards, and engineering practices that power enterprise reporting, governed metrics, and AI-enabled analytics at Contentstack.
In this high-impact role, you’ll establish scalable, reusable modeling frameworks across Snowflake and dbt, lead the implementation of governed semantic models, and partner with Data Engineering, BI & Analytics, Revenue Operations, Finance, and executive leadership to build a trusted foundation for data-driven decision-making.
If you’re passionate about modern analytics architecture, translating complex business needs into scalable solutions, and enabling the next generation of AI-powered analytics, we’d love to hear from you! Here’s what you’ll be doing:
Lead analytical architecture and governance: Define enterprise modeling standards across staging, intermediate, dimensional, fact, semantic, and mart layers. Establish conventions for model grain, naming, ownership, lineage, and documentation, and lead architectural design reviews.
Build governed data models and semantic layers: Design and implement reusable business entities, semantic models, and enterprise metrics that support consistent reporting, self-service analytics, applications, and AI-enabled workflows.
Establish analytics engineering best practices: Set standards for dbt development, testing, Git workflows, CI/CD, deployment reliability, model performance, and observability to improve scalability and maintainability.
Enable secure, reliable data access: Design governed access patterns for applications, AI agents, and self-service tools consuming Snowflake data, including role-based access control (RBAC), APIs, service layers, and query optimization.
Partner across the business: Work closely with Data Engineering, BI & Analytics, Revenue Operations, Finance, and executive stakeholders to translate business requirements into trustworthy data models and scalable analytics solutions.
Mentor and enable the team: Guide analytics engineers on modular architecture, semantic implementation, reusable modeling patterns, and modern analytics engineering practices.
Drive platform evolution: Evaluate tools, semantic technologies, governance capabilities, and architectural improvements that support long-term scalability while reducing technical debt.
What Really Gets Us Excited About You
5-8 years of experience in data engineering, analytics engineering, or data architecture, including at least 3 years in an architect capacity with direct ownership of an analytical platform.
Deep, hands-on expertise in Snowflake architecture, including virtual warehouse design, RBAC, materialization strategies, dynamic tables, and query performance optimization.
Expert-level experience with dbt, including staging/intermediate/mart conventions, Jinja macros, incremental models, testing, documentation, and reusable modeling patterns.
Strong understanding of dimensional and semantic modeling, with the ability to select and justify approaches based on business and analytical needs.
Proven experience designing and deploying production semantic layers and governed metrics across BI platforms, analytics applications, and AI-enabled workflows, including text-to-SQL and MCP-based integrations.
Advanced SQL skills and experience with Python, along with familiarity with dbt Cloud, Fivetran, Git, CI/CD, and cloud-native analytics environments.
Experience designing secure data 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 explain architectural decisions to technical teams, executive leaders, and cross-functional stakeholders.
Experience collaborating with globally distributed teams across the US, Europe, and India.
Snowflake SnowPro Core or Advanced certification; dbt Certified Data Architect or Analytics Engineer certification.
Experience with Snowflake Cortex and Snowpark ML for in-warehouse AI/ML workloads.
Experience working with Salesforce as a source system, including dimensional modeling for go-to-market (GTM) data.
Experience with retrieval-augmented generation (RAG) architectures that connect large language models to governed analytical data.
Familiarity with BI tools such as Tableau, Looker, or Power BI.
Experience implementing data governance frameworks, including data catalogs, column-level lineage, and row-level security.
You value a fun, collaborative, and innovative culture!
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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