Snowflake Data Platform Architect

Experis ManpowerGroup Sp. z o.o.; Town of Poland (NY); On-site; USD 120,000 - 150,000; Full time

Job summary

Experis ManpowerGroup Sp. z o.o. is seeking a qualified data engineer to design and maintain a Snowflake-based data platform in the New York area. The role focuses on scalable architectures, secure data processing, and robust pipelines to support analytics use cases.

You will implement ETL/ELT processes, develop data models, and collaborate with stakeholders to translate business needs into concrete data solutions while adhering to architectural guidelines and best practices.

Qualifications

• Proven experience using Snowflake as a data engineering platform.
• Strong knowledge of ETL/ELT, data integration, and pipeline development.
• Hands-on data modeling experience and scalable data solutions.

Responsibilities

• Design, develop, and maintain scalable Snowflake data platform architectures with data models and CI/CD.
• Define and implement Snowflake solutions aligned with business and technical requirements.
• Evaluate Snowflake components to meet scalability, performance, and security needs.
• Design and implement robust ETL/ELT data pipelines to support ingestion and analytics.
• Develop and optimize data models ensuring data quality and usability across domains.
• Implement security best practices across Snowflake and Azure environments.
• Collaborate with stakeholders to translate data needs into technical solutions.
• Provide delivery oversight to ensure timely, quality outcomes and architectural alignment.
• Support platform improvements through performance optimization and automation.

Skills

Snowflake data engineering

ETL/ELT

Data modeling

Data integration

Pipeline development

Security best practices

Tools

Snowflake

Azure

CI/CD

Job description

Experis ManpowerGroup Sp. z o.o. is seeking a qualified data engineer to design and maintain a Snowflake-based data platform in the New York area. The role focuses on scalable architectures, secure data processing, and robust pipelines to support analytics use cases.

You will implement ETL/ELT processes, develop data models, and collaborate with stakeholders to translate business needs into concrete data solutions while adhering to architectural guidelines and best practices.