Snowflake Data Architect – Cortex AI
@ PB consultingSnowflake Data Architect – Cortex AI
About the job
Cortex AI is looking for a senior Snowflake Data Architect with expertise in enterprise data architecture, modeling, and cloud data platforms to build scalable analytics solutions and support AI integrations.
Requirements
- 7–10 years data engineering or architecture
- 3+ years with Snowflake
- Expertise in SQL and cloud warehousing
- Designing data models and pipelines
- BI platform experience
Qualifications
- Bachelor's degree in related field
- Strong problem-solving skills
- Excellent communication skills
- Experience with SaaS data sources
- Understanding of data governance
Full job description
We are seeking a highly experienced Senior Snowflake Data Architect with strong expertise in enterprise data architecture, analytics, data modeling, and modern cloud data platforms. The ideal candidate will have hands-on experience with Snowflake, advanced SQL, dimensional data modeling, ELT pipelines, BI enablement, and enterprise data integration.
Experience with Snowflake Cortex AI and modern AI/ML capabilities within the Snowflake platform is highly desirable. The architect will work closely with technical leaders and engineering teams to design scalable, analytics-ready data solutions and support the onboarding of enterprise data sources and business domains into Snowflake.
Primary Responsibilities
- Serve as a senior technical subject matter expert for Snowflake data architecture and enterprise analytics platforms.
- Design scalable and secure Snowflake architectures aligned with enterprise data and analytics requirements.
- Lead the onboarding and integration of enterprise systems and business domains into Snowflake.
- Design analytics-ready data models, dimensional models, semantic layers, and reusable data structures.
- Develop and optimize SQL queries, data transformations, views, and data processing workflows.
- Design and support ELT-based data pipelines for ingestion and transformation of enterprise data.
- Enable data consumption and reporting through BI platforms such as Power BI and Sigma.
- Develop semantic views and curated datasets to support analytics, reporting, and self-service BI.
- Integrate data from enterprise SaaS applications and other operational data sources.
- Evaluate architectural options, identify technical risks, and communicate key trade-offs to senior technical stakeholders.
- Establish and promote data architecture, modeling, governance, and development standards.
- Collaborate with data engineers, BI developers, platform architects, application teams, and other technical stakeholders.
- Evaluate and support emerging Snowflake AI capabilities, including Snowflake Cortex, where applicable.
- Contribute to technical documentation, architecture diagrams, data models, standards, and implementation guidelines.
Required Qualifications
- 7–10 years of experience in data engineering, data architecture, analytics, or related disciplines.
- 3+ years of hands-on experience working with Snowflake in enterprise environments.
- Strong expertise in Snowflake architecture, SQL, and cloud data warehousing.
- Strong understanding of relational data warehouse concepts and modern data architecture.
- Proven experience designing dimensional data models and semantic data layers.
- Experience designing and supporting ELT-based data pipelines.
- Experience integrating enterprise applications and SaaS data sources into analytics platforms.
- Experience enabling BI and analytics platforms such as Power BI or Sigma.
- Strong understanding of data integration, transformation, data quality, and analytics enablement.
- Strong analytical, problem-solving, communication, and collaboration skills.
Preferred Qualifications
- Hands-on experience with Snowflake Cortex AI and related Snowflake AI/ML capabilities.
- Experience with Salesforce Data Cloud / Data 360 and Salesforce data models.
- Experience with enterprise-scale Snowflake implementations involving multiple teams and business domains.
- Knowledge of modern data governance, data security, and data management practices.
- Experience with Snowflake performance optimization and cost management.
- Familiarity with modern data engineering and orchestration tools.
- SnowPro Core, SnowPro Advanced Architect, or other relevant Snowflake certifications.
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