Senior Business Intelligence Data Architect
C
ContentstackData analytics
Remote - Netherlands or PortgualFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 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.
- Required Skills
- PythonSQLGitSnowflakeCI/CDdbt
Requirements
- Have 8-12 years of experience in data engineering, analytics engineering, or data architecture.
- Have at least 3 years in an architect capacity with direct ownership of an analytical platform.
- Bring hands-on expertise in Snowflake architecture, including virtual warehouse design, RBAC, materialization strategies, dynamic tables, and query performance optimization.
- Have expert-level dbt experience, including model conventions, Jinja macros, incremental models, testing, documentation, and reusable patterns.
- Understand dimensional and semantic modeling and how to choose approaches for business and analytical needs.
- Have experience designing and deploying production semantic layers and governed metrics across BI platforms, analytics applications, and AI-enabled workflows.
- Have advanced SQL skills and experience with Python.
- Be familiar with dbt Cloud, Fivetran, Git, CI/CD, and cloud-native analytics environments.
- Have experience designing secure Snowflake data access patterns, including APIs, service layers, RBAC, query performance, and governed semantic access.
- Have Snowflake SnowPro Core or Advanced certification, or dbt Certified Data Architect or Analytics Engineer certification.
Responsibilities
- 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.
- Design and implement reusable business entities, semantic models, and enterprise metrics.
- Set 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.
- Partner with Data Engineering, BI & Analytics, Revenue Operations, Finance, and executive stakeholders to translate business requirements into data models and analytics solutions.
- Guide analytics engineers on modular architecture, semantic implementation, and reusable modeling patterns.
- Evaluate tools, semantic technologies, governance capabilities, and architectural improvements.
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