Data Architect (Snowflake)

About The Role In this role, you will contribute to designing and implementing scalable cloud-based data platforms with a strong focus on Snowflake and modern ELT architectures. You will collaborate with technical and business stakeholders to design reliable data solutions, optimize data platforms, and support organizations in building modern analytics ecosystems within AWS environments. You will participate throughout the full project lifecycle, from solution design and proof of concepts to production implementation. Responsibilities Design and support implementation of scalable data platforms and analytics solutions using Snowflake and AWS services Design, develop, and optimize ELT pipelines and data transformation workflows using dbt and SQL Define data models, data warehouse architectures, and source-to-target mappings to support analytics and reporting workloads Collaborate with stakeholders to gather requirements and translate business needs into scalable technical solutions Support data ingestion, transformation, and orchestration processes across cloud-based data platforms Participate in architecture discussions and contribute to data platform evolution, performance optimization, and engineering best practices Ensure data quality, governance, and maintainability through automated testing, documentation, and CI/CD practices Create and maintain architecture documentation, data models, and technical design artifacts Participate throughout the full project lifecycle, from discovery and PoCs to production implementation Requirements Proven experience designing modern data platforms and cloud-based data warehouse solutions Strong hands-on experience with Snowflake, including data modeling, performance optimization, and analytics workloads Experience designing and building ELT pipelines using dbt, SQL, and modern data engineering practices Strong expertise with AWS services supporting modern data platforms Proficiency in SQL and Python for data engineering and automation Experience with orchestration tools such as Apache Airflow or MWAA Understanding of data warehousing concepts, dimensional modeling, and modern data architecture patterns Familiarity with CI/CD practices, data quality validation, and version control for data engineering workflows 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.