Pre-Sales Architect - Data Engineering

$129,000 - $184,800/Yr

Snowflake Computing

Full-time - Senior

Remote

Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services

About the position

The Pre-Sales Architect - Data Engineering at Snowflake is a key technical role within the Professional Services team, responsible for engaging with customers to understand their data engineering needs and providing high-level architectural solutions using Snowflake's capabilities. This position involves collaborating with sales teams to scope complex engagements, enabling sellers with technical knowledge, and maintaining a deep understanding of data engineering best practices and competitive technologies.

Responsibilities

• Be a technical expert on all aspects of Snowflake in relation to data engineering workloads.
• Work with Professional Services Practice Directors and Managers on sales pursuits to understand customer requirements.
• Present high level architecture solutions using Snowflake.
• Scope and present project plans and effort estimates to deliver data engineering solutions.
• Consult with customers in sales workshops using SQL, Python, Java, and/or Scala to understand their data engineering workload/use case.
• Maintain a deep understanding of competitive and complementary technologies and vendors within the data engineering space.
• Provide guidance on how to resolve customer-specific technical challenges.
• Assist in writing Statements of Work.
• Identify selling patterns within the data engineering space and create go-to-market options for PS Sellers.
• Enable PS Sellers with technical knowledge to scale the ability to sell data engineering solutions.
• Collaborate with Product Management, Engineering, and Marketing to continuously improve Snowflake's products and marketing.

Requirements

• Minimum 10 years experience working with customers in a pre-sales or post-sales technical role.
• Outstanding skills presenting to both technical and executive audiences.
• Thorough understanding of the complete Data Engineering life-cycle.
• Experience and understanding of at least one public cloud platform (AWS, Azure or GCP).
• Experience with Databricks/Apache Spark.
• Hands-on scripting experience with SQL and at least one of the following: Python, Java or Scala.
• Experience with libraries such as Pandas, PyTorch, TensorFlow, SciKit-Learn or similar.
• University degree in data science, computer science, engineering, mathematics or related fields, or equivalent experience.

Nice-to-haves

• Experience with Snowflake Snowpark.
• Experience in Data Science.
• Experience implementing data pipelines using ETL tools.
• Experience working with RDBMS data warehouses.
• Proven success at enterprise software.
• Vertical expertise in a core vertical such as FSI, Retail, Manufacturing etc.

Benefits

• Medical, dental, vision, life, and disability insurance.
• 401(k) retirement plan.
• Flexible spending & health savings account.
• At least 12 paid holidays.
• Paid time off.
• Parental leave.
• Employee assistance program.
• Other company benefits.