Staff Designated Support Engineer

Responsibilities

• Provide hands-on support for customer needs post-Snowflake deployment, including quick start consultations, issue resolutions, account health monitoring, and critical event support.
• Develop deep understanding of customer's product integration architecture, workloads, and business objectives.
• Design, review, and execute use cases aligned with Snowflake best practices, product features, and functionality.
• Deliver guidance on resolving customer-specific technical challenges.
• Monitor, analyze, and provide actionable recommendations for query performance optimization and cost optimization (warehouse configuration and utilization).
• Work with System Integrator consultants on system integration, positioning, and deployment of Snowflake.
• Own release readiness for priority support customers, lead disaster recovery drills, and provide hands-on migration support.
• Drive high-quality issue resolution, root cause analyses (RCAs), and serve as the internal customer advocate.
• Establish regular technical and executive touchpoints with customers for updates and forward-looking guidance.
• Partner cross-functionally with Product Management, Engineering, and Marketing to surface customer insights and improve products/services.
• Apply AI-powered tooling for triage, log analysis, response drafting, and trend detection; validate outputs and escalate appropriately.
• Be available on-call as needed for customer success.

Requirements

• 7+ years of experience in Technical Support, Solutions Architecture, Data Engineering, or similar customer-facing technical role.
• Bachelor's or Master's degree in Computer Science, MIS, or related field (or equivalent experience).
• Proven success managing enterprise customer relationships as a trusted technical advisor, including communicating with and influencing technical and executive audiences.
• Advanced SQL expertise, including query debugging, optimization, window functions, and performance tuning.
• Strong RDBMS fundamentals: data types, aggregations, execution plans, workload management, and database performance.
• Hands-on experience with distributed or MPP database platforms.
• Experience with ETL/ELT tools and BI/analytics platforms (e.g., AWS Glue, Azure Data Factory, Informatica, Matillion, Fivetran, Tableau).
• Experience working with large-scale IaaS platforms (AWS, Azure, GCP).
• AI fluency: ability to use AI-assisted workflows for triage, analysis, and response drafting, with critical validation of outputs.
• High emotional intelligence (EQ), empathy, strong customer advocacy skills, and adaptability in a fast-moving environment.

Nice-to-Haves

• Experience with DevOps or DataOps tooling such as Git, Jenkins, or Terraform.
• Hands-on experience troubleshooting database connectivity (drivers, connectors, client software) and cloud data migrations.
• Solid understanding of internet fundamentals (TCP/IP, HTTP/S, SFTP, DNS) and diagnostic tools for connectivity issues.
• Experience with one or more of: Python, Java, JavaScript, Scala, or Spark.
• Familiarity with common BI and data exploration tools (Power BI, Tableau, MicroStrategy, Business Objects).