Senior Professional Services Sales Solutions Architect

Responsibilities

• Present Snowflake technology and vision to executives and technical contributors.
• Position as Trusted Advisor to key customer stakeholders for business outcomes.
• Partner with Practice Directors and Managers to identify, iterate, and scope proposals and Statements of Work.
• Collaborate with sales executives on opportunity development and account strategy.
• Build trust through on-site workshops, video meetings, deep-dive technical assistance, and public evangelism.
• Collect customer themes to inform delivery teams and identify new service offerings.
• Drive project teams to accelerate Snowflake adoption.
• Demonstrate Snowflake value in engagements from demos to implementations.
• Create repeatable processes and documentation from customer engagements.
• Develop industry-based solutions for broader customer value.
• Follow best practices including knowledge transfer.
• Maintain understanding of competitive technologies and positioning.

Requirements

• University degree in computer science, engineering, mathematics or related fields, or equivalent experience.
• Minimum 5 years as solutions architect, data architect, database administrator, or data engineer.
• Minimum 2 years practical Snowflake experience in services engagements.
• Minimum 2 years practical experience with AWS, Azure, or GCP.
• Understanding of data analytics stack (ETL to BI).
• Hands-on technical experience (SQL, data warehousing, cloud data, analytics, ML/AI).
• Extensive knowledge of large-scale database technology (Snowflake, Netezza, etc.) with data science/AI/ML, OR AI/ML model development (Sagemaker, etc.) with libraries (sklearn, xgboost, pytorch, pandas).
• Software development with Python, Java, Spark, scripting.
• Proficiency in Snowflake data security, access controls.
• Consulting experience.
• Impeccable communication skills for technologists to C-suite.

Nice-to-Haves

• Big 5 Consulting experience.
• Selling/supporting sales of technical services at enterprise level.
• Non-relational platforms (Hadoop, HBase).
• BI tools (Microstrategy, Looker, Tableau).
• OLAP data modeling.
• Vertical expertise (Financial Services, Retail, etc.).
• Relevant certifications (cloud, data tech, etc.).