Be a technical guide on all aspects of Snowflake
Deploy Snowflake following best practices, including ensuring knowledge transfer so that customers are properly enabled and are able to extend the capabilities of Snowflake on their own
Work hands-on with customers to demonstrate and communicate implementation best practices on Snowflake technology
Maintain deep understanding of competitive and complementary technologies and vendors and how to position Snowflake in relation to them
Work with System Integrator consultants at a deep technical level to successfully position and deploy Snowflake in customer environments
Provide guidance on how to resolve customer-specific technical challenges
Support other members of the Professional Services team develop their expertise
Collaborate with Product Management, Engineering, and Marketing to continuously improve Snowflake's products and marketing.
OUR IDEAL SOLUTIONS ARCHITECT WILL HAVE:
University degree in computer science, engineering, mathematics or related fields, or equivalent experience
Outstanding skills presenting to both technical and executive audiences, whether impromptu on a whiteboard or using presentations and demos
Understanding of complete data analytics stack and workflow, from ETL to data platform design to BI and analytics tools
Strong skills in databases, data warehouses, and data processing
Extensive hands-on expertise with SQL and SQL analytics
Experience and track record of success selling data and/or analytics software to enterprise customers; includes proven skills identifying key stakeholders, winning value propositions, and compelling events
Extensive knowledge of and experience with large-scale database technology (e.g. Netezza, Exadata, Teradata, Greenplum, etc.)
Software development experience with C/C++ or Java.Scripting experience with Python, Ruby, Perl, Bash.
Native German language
Need to be able to travel frequently
BONUS POINTS FOR THE FOLLOWING:
Experience with non-relational platforms and tools for large-scale data processing (e.g. Hadoop, HBase)
Familiarity and experience with common BI and data exploration tools (e.g. Microstrategy, Business Objects, Tableau)
Experience and understanding of large-scale infrastructure-as-a-service platforms (e.g. Amazon AWS, Microsoft Azure, OpenStack, etc.)
Experience implementing ETL pipelines using custom and packaged tools
Experience using AWS services such as S3, Kinesis, Elastic MapReduce, Data pipeline
Experience selling enterprise SaaS software
* Shown success at enterprise software.
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