Snowflake
Snowflake is a cloud-based data-warehousing company that provides an innovative platform for data storage, processing, and analytics. It enables organizations to handle large volumes of data efficiently, facilitating insights and business intelligence. Snowflake's architecture supports various data workloads, making it a versatile solution for enterprises looking to leverage their data for strategic decision-making.
Data Warehousing • Cloud • Analytics • Data Lake • Marketing Analytics
Senior Solutions Engineer
February 21
Snowflake
Snowflake is a cloud-based data-warehousing company that provides an innovative platform for data storage, processing, and analytics. It enables organizations to handle large volumes of data efficiently, facilitating insights and business intelligence. Snowflake's architecture supports various data workloads, making it a versatile solution for enterprises looking to leverage their data for strategic decision-making.
Data Warehousing • Cloud • Analytics • Data Lake • Marketing Analytics
📋 Description
• Build the future of the AI Data Cloud. Join the Snowflake team. • We're leading the data revolution, building the world’s best data and applications platform. • Success in this role requires relationship management, program execution, goal-setting, and tracking progress. • You will help shape and deliver a strategy to build mindshare with Snowflake’s SI partners. • Help Solution Providers/Practice Leads with the technical strategies that enable them to sell their offerings on Snowflake. • Conversations with other technologists, providing presentations at the C-level. • Collaborate with partners to develop Snowflake solutions in customer engagements. You will be working with our partners to create assets and demos, build hands-on POCs and pitch Snowflake solutions. • Help develop and launch joint differentiated solution offerings with SI Partners.
🎯 Requirements
• 5+ years industry experience designing, building and supporting large-scale systems in production. • Strong CS fundamentals, including proficiency with data structures, algorithms, and distributed systems. • Production level hands on expertise in developing and deploying PySpark or Scala and SQL to build ELT/data pipelines into production environments. Staying current with the latest Spark updates and best practices. • Hands on experience in designing and building highly scalable data pipelines using Spark, Kafka to ingest data from various systems. • Experience with integration platforms like Matillion, FiveTran, Informatica, dbtCloud etc. • Experience with database technologies. • Hands-on technical experience with DevOps and CI/CD processes and tools, such as Azure DevOps, Jenkins, AWS CodePipeline, and Google Cloud Build. • Strong experience with major cloud platforms and tooling, especially Azure or AWS, or Google Cloud. • Experience using Big Data or Cloud integration technologies such as Matillion, Azure Data Factory, AWS Glue, AWS Lambda, etc. • Experience with AI/ML use cases is a plus. • Fluency in multiple programming languages is a big plus. • Knowledge of database internals is a plus. • Experience working with cross teams and product managers. • BS/MS/PhD in Computer Science or related majors. • Excellent verbal and written communications skills in English.
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