Data Architect (Snowflake)

About The Role In this role, you will help design and implement modern cloud-based data platforms that enable scalable analytics and data-driven decision-making. You will work with Snowflake, AWS, dbt, SQL, and Python to build reliable ELT solutions, collaborating with technical and business stakeholders throughout the full project lifecycle, from discovery and proof of concepts to production deployment.

Responsibilities

• Design and support the implementation of scalable data platforms and analytics solutions using Snowflake and AWS services
• Develop, optimize, and maintain ELT pipelines and data transformation workflows with dbt, SQL, and modern data engineering practices to ensure reliable and efficient data delivery
• Partner with architects, engineers, and business stakeholders to gather requirements and translate business objectives into scalable technical solutions
• Define data models, data warehouse architectures, and source-to-target mappings that support reporting, analytics, and data consumption needs
• Support data ingestion, transformation, orchestration, and monitoring processes across cloud-based environments
• Contribute to architecture discussions, platform evolution initiatives, and performance optimization efforts to improve scalability and maintainability
• Implement data quality, governance, testing, and CI/CD practices to ensure trusted and production-ready data assets
• Create and maintain technical documentation, architecture artifacts, and data models while participating in all project phases from discovery and PoCs to production implementation

Requirements

• Proven experience designing modern data platforms and cloud-based data warehouse solutions
• Strong hands-on expertise with Snowflake, including data modeling, analytics workloads, and performance optimization
• Experience designing and building ELT pipelines using dbt, SQL, and modern data engineering methodologies
• Strong knowledge of AWS services and cloud-native technologies supporting data and analytics platforms
• Proficiency in SQL and Python for data engineering, automation, and data processing
• Experience with orchestration tools such as Apache Airflow or MWAA
• Solid understanding of data warehousing principles, dimensional modeling, and modern data architecture patterns
• Familiarity with CI/CD practices, data quality validation frameworks, automated testing, and version control workflows
• Strong collaboration, communication, and problem-solving skills with an ability to work effectively with cross-functional teams
• Upper-intermediate or higher level of English

SoftServe is an equal opportunity employer. Qualified applicants will receive consideration regardless of race, color, ancestry, ethnicity, national origin, religion, sex, sexual orientation, gender identity or expression, age, citizenship, disability, health condition, marital or family status, veteran status, or any other characteristic protected by applicable law.