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Snowflake's Solution Engineering organization is seeking a Principal Data Platform Architect to provide technical leadership in designing and architecting the Snowflake Cloud Data Platform as a critical component of enterprise data ecosystems. This role bridges technical and business contexts, working directly with sales teams, prospects, and customers throughout the sales cycle—from initial discovery and compelling demonstrations through enterprise proof-of-concepts to design and implementation support.
You will apply deep multi-cloud data architecture expertise while presenting Snowflake technology and vision to both executives and technical contributors at strategic prospects, customers, and partners. Your responsibilities include hands-on engagement with prospects and customers to demonstrate and communicate Snowflake's value, maintaining current knowledge of competitive and complementary technologies, and collaborating with Product Management, Engineering, and Marketing to continuously improve Snowflake's offerings.
Required qualifications include 10+ years of architecture and data engineering experience in the Enterprise Data space, plus 5+ years in a pre-sales environment (Sales Engineer, Solutions Engineer, Solutions Architect, or equivalent). You must possess outstanding presentation skills for both technical and executive audiences, with the ability to connect customer business problems to Snowflake solutions through deep discovery of their architecture frameworks.
Technical expertise required: broad experience with large-scale database and data warehouse technologies, ETL, analytics, and cloud technologies (Data Lake, Data Mesh, Data Fabric); hands-on development with SQL, Python, Pandas, Spark, PySpark, Hadoop, Hive, and other big data technologies; deep understanding of data integration services and tools (Apache NiFi, Matillion, Fivetran, Qlik, Informatica); familiarity with streaming technologies (Kafka, Flink, Spark Streaming, Kinesis) and real-time/near-real-time use cases; and strong architectural expertise in designing interoperable data lakehouse architectures with Iceberg, Delta, and Parquet. A Bachelor's degree is required; a Master's degree in computer science, engineering, mathematics, or related fields is preferred.
