Senior Business Intelligence Data Architect

Contentstack

. Define enterprise modeling standards across staging, intermediate, dimensional, fact, semantic, and mart layers .

Posted 10/26/2026full-timeRemote • Netherlands, PortugalSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates deep expertise in Snowflake architecture and dbt development, with a strong focus on designing scalable analytics solutions and implementing data governance frameworks. Proven ability to lead architectural design reviews and collaborate effectively with cross-functional teams.

Highest-signal resume keywords

Snowflake ArchitectureDbt DevelopmentDimensional ModelingAdvanced SQL SkillsData Governance Frameworks

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringAnalytics EngineeringData ArchitectureSemantic ModelingQuery Performance OptimizationMaterialization StrategiesAPIsRBACIncremental ModelsDynamic Tables

Soft Skills

Strong Written CommunicationStrong Verbal CommunicationCollaboration

Tools & Technologies

SnowflakeDbt CloudFivetranGitCI/CDTableauLookerPower BISnowflake CortexSnowpark ML

Certifications & Qualifications

Snowflake SnowPro Core CertificationSnowflake SnowPro Advanced CertificationDbt Certified Data ArchitectDbt Certified Analytics Engineer

Industry Keywords

Enterprise Modeling StandardsBusiness EntitiesSemantic ModelsGoverned MetricsAnalytics ApplicationsAI-Enabled WorkflowsData CatalogsColumn-Level LineageRow-Level SecurityRetrieval-Augmented Generation

Tech Stack

Tools & technologies

CloudPythonSnowflakeSQLTableau

About the role

Key responsibilities & impact

Define enterprise modeling standards across staging, intermediate, dimensional, fact, semantic, and mart layers
Establish conventions for model grain, naming, ownership, lineage, and documentation
Lead architectural design reviews
Design and implement reusable business entities, semantic models, and enterprise metrics
Establish standards for dbt development, testing, Git workflows, CI/CD, deployment reliability, model performance, and observability
Design governed access patterns for applications, AI agents, and self-service tools consuming Snowflake data, including RBAC, APIs, service layers, and query optimization
Partner with Data Engineering, BI & Analytics, Revenue Operations, Finance, and executive stakeholders
Translate business requirements into trustworthy data models and scalable analytics solutions
Guide analytics engineers on architecture, semantic implementation, reusable modeling patterns, and analytics engineering practices
Evaluate tools, semantic technologies, governance capabilities, and architectural improvements
Reduce technical debt and support long-term platform scalability

Requirements

What you’ll need

8-12 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
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
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
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 GTM data
Experience with retrieval-augmented generation (RAG) architectures
Familiarity with Tableau, Looker, or Power BI
Experience implementing data governance frameworks, including data catalogs, column-level lineage, and row-level security
Value a fun, collaborative, and innovative culture

Benefits

Comp & perks

Interesting, challenging work with opportunities to learn and grow
Spontaneous office happy hours
Organized outings
Community volunteer opportunities
Opportunity to contribute and have your voice heard
Regular updates about the business and its performance