Senior Data Platform Architect

July 2

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Snowflake

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Cloud Computing • Data Analytics • SaaS

Snowflake is a cloud-based data-warehousing company that provides a platform for data storage, processing, and analytics. It allows businesses to store data in a centralized location and perform complex queries and analytics on that data efficiently. Snowflake is designed to handle a wide range of data workloads and can scale dynamically to meet the needs of growing businesses.

5001 - 10000 employees

Founded 2012

☁️ SaaS

📋 Description

• Apply your multi-cloud data architecture expertise while presenting Snowflake technology and vision to executives and technical contributors at strategic prospects, customers, and partners • Work hands-on with prospects and customers to demonstrate and communicate the value of Snowflake technology throughout the sales cycle, from demo to proof of concept to design and implementation • Immerse yourself in the ever-evolving industry, maintaining a deep understanding of competitive and complementary technologies and vendors and how to position Snowflake in relation to them • Collaborate with Product Management, Engineering, and Marketing to continuously improve Snowflake’s products and marketing

🎯 Requirements

• 5+ years of architecture and data engineering experience within the Enterprise Data space • 5+ years experience within a pre-sales environment • Outstanding presenting skills to both technical and executive audiences, whether impromptu on a whiteboard or using presentations and demos. • Broad range of experience within large-scale Database and/or Data Warehouse technology, ETL, analytics and cloud technologies. For example, Data Lake, Data Mesh, Data Fabric • Hands on Development experience with technologies such as SQL, Python, Pandas, Spark, PySpark, Hadoop, Hive and any other Big data technologies • Ability to connect a customer’s specific business problems and Snowflake’s solutions • Ability to do deep discovery of customer’s architecture framework and connect those with Snowflake Data Architecture. • Must have some prior knowledge of Data Engineering tools for ingestion, transformation and curation • Familiarity with real-time or near real time use cases (ex. CDC) and technologies (ex. Kafka, Flink) and deep understanding of integration services and tools for building ETL and ELT data pipelines and its orchestration technologies such as Matillion, Fivetran, Airflow, Informatica, etc.. • Strong architectural expertise in data engineering to confidently present and demo to business executives and technical audiences, and effectively handle any impromptu questions