The Applied Performance Group provides a highly strategic function at Snowflake, with direct impact to our product direction, as well as to our bottom line. Performance engineers are a key bridge between Engineering and our Sales organization- they are called on to help with our most challenging and complicated performance issues and help deliver some of our biggest deals. In addition, they will be at the cutting edge of innovation at Snowflake- pioneering Snowflake deployments with the newest tech and working with Engineering and Product Management to continuously improve the product and ensure we continue building the best Cloud Data Platform in the industry.
A successful Performance Engineer will have a broad range of skills and experience ranging from strong SQL skills, knowledge of database internals, data warehouse implementation, data architecture, ETL, security, performance analysis, analytics, etc. He/she will have the insight to make the connection between a customer’s specific 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 a small, but critical team in the Engineering organization. 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 Performance Engineer at Snowflake you will:
- Assist sales engineers and Support to determine and resolve SQL performance issues.
- Partner closely with sales engineers and solutions teams to deliver guidance on POC implementations, best practices, white papers, playbooks.
- Collaborate with Product Management and Engineering to continuously improve Snowflake’s products and eco-system roadmaps.
- Engage directly to hands-on build solutions for our most critical and impactful customer POC’s.
- Maintain deep understanding of existing and complementary technologies and vendors and develop best practices for Snowflake to integrate with them.
Our ideal Performance Engineer will have:
- Minimum 5 years of experience in technical role delivering Database or Data Warehouse implementations.
- Deep technical expertise in databases, database internals, data warehouses, and data processing with an understanding of database query plans and performance analysis.
- Experience and ability to work directly with customers.
- Strong communication skills, able to effectively communicate ideas and technical concepts to both technical and executive audiences.
- Deep understanding of complete data analytics stack and workflow, from ETL to data platform design to BI and analytics tools.
- Strong SQL language experience, ability to write and troubleshoot and tune complex SQL Queries.
- Extensive knowledge of and experience with large-scale, MPP database technology (e.g. Netezza, Exadata, Teradata, Greenplum).
- Scripting experience with Python, Ruby, Perl, Bash.
- 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. Spark, 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).
- Experience implementing ETL pipelines using custom and packaged tools.
- Experience using AWS services such as S3, Kinesis, Elastic MapReduce, Data Pipeline.