The Snowflake Sales Engineer will work hand-in-hand with Sales, Product, Engineering, and Marketing to help us bring our first product to market and grow the company. She/he will be responsible for providing the deep technical expertise to make Snowflake customers successful. This sales engineer will have a broad range of skills and experience ranging from writing code in SQL and other languages, to data architecture, ETL/ELT, networking, security, performance analysis, architecting scalable solutions, business intelligence, analytics, etc. He/she will have the business skills to discover a customers’ specific business problems and quantify the associated business pains; the insight to make the connection between the discovered business problems and Snowflake’s solution; the customer-facing skills to communicate that connection and vision to a wide variety of technical and executive audiences; and the technical skills to be able to not only build demos and execute proof-of-concepts but also to provide consultative assistance on architecture and implementation.
The person we’re looking for shares our passion about reinventing the data platform and thrives in the dynamic environment that comes with being part of an innovative startup from its early days. That means having the flexibility and willingness to jump in and get done what needs to be done to make Snowflake and our customers successful. It means keeping up to date on the ever-evolving technologies for data and analytics in order to be an authoritative resource for both Snowflake and customers. And it means working collaboratively with a broad range of people both inside and outside the company.
As a Sales Engineer at Snowflake you will:
- Run discovery sessions as part of the sales process to uncover specific business problems and quantify the associated business pains.
- Present Snowflake technology and vision to executives and technical contributors at prospects and customers.
- 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.
- Work hand-in-hand with the sales team to manage the sales process with customers of varying size, complexity and need. This includes documenting information gathered and maintaining data in our CRM.
- Maintain 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.
Our ideal Sales Engineer will have:
- Minimum 6 years of experience working with customers in a pre-sales or post-sales technical role.
- Hold a bachelor’s degree in an IT-related field (science, information sciences, engineering, etc).
- Outstanding business acumen to understand customers’ business processes across a range of industries, and to help identify specific business challenges.
- Outstanding skills presenting to both technical and executive audiences, whether impromptu on a whiteboard or using presentations and demos. Presentations will range from 1:1 to boardrooms to auditoriums at industry events.
- Experience creating training materials and conducting training classes.
- 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.
- 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, Redshift, SQL DW, Google BigQuery).
- Extensive knowledge of and experience with public infrastructure-as-a-service platforms (e.g. Amazon AWS, Azure, Google GCP). Certification for these platforms preferred.
- University degree in computer science, engineering, mathematics or related fields, or equivalent experience.
Bonus points for experience with the following:
- Experience with non-relational platforms and tools for large-scale data processing (e.g. Hadoop, HBase, Cloudera, HortonWorks, MapR, ).
- Familiarity and experience with common BI and data exploration tools (e.g. Microstrategy, Business Objects, Tableau, PowerBI, Qlik, ThoughtSpot).
- Familiarity and experience with common data science, AI and ML platforms and frameworks (e.g. Databricks, SageMaker, DataRobot, Qubole, DataIku, GoogleML, AzureML).
- Experience implementing ETL pipelines using custom and packaged tools.
- Experience using AWS services such as S3, EC2, IAM, Glue, SQS/Kinesis, VPC networking.
- Experience using Azure services such as ABS, ADLS, Azure AD, ADF, Event Grid, VNet networking.
- Experience using GCP services such as GCS, GCE, Cloud IAM, Pub/Sub, DataFlow, VPC networking.
- Experience selling enterprise SaaS software.
- Proven success at enterprise software startups.