Data Engineering - Applied Field Engineer - CA - Menlo Park - Remote

Location: Remote from the United States; associated with Menlo Park, California

Salary: $189,000–$248,062 per year

Company

Snowflake provides a cloud data platform that helps enterprises build and operate data architectures, analytics, and lakehouse workloads.

What you will do

• Provide technical leadership in designing and architecting Snowflake cloud data platform solutions within enterprise data ecosystems.
• Work with sales teams, prospects, customers, partners, and business and technical executives throughout sales cycles.
• Deliver value-based demonstrations, support enterprise proofs of concept, and contribute to design and implementation activities.
• Present multi-cloud data architecture expertise and Snowflake technology across data ingestion, transformation, analytics, and lakehouse workloads.
• Research competitive and complementary technologies and collaborate with Product Management, Engineering, and Marketing.

Requirements

• 10+ years of enterprise data architecture and data engineering experience.
• 5+ years of experience in a pre-sales role such as Sales Engineer, Solutions Engineer, or Solutions Architect.
• Strong presentation, customer discovery, architectural design, and executive communication skills.
• Experience with large-scale databases, data warehouses, ETL, analytics, cloud technologies, data lakes, data mesh, or data fabric.
• Hands-on experience with SQL, Python, Pandas, Spark, PySpark, Hadoop, Hive, and other big data technologies.
• Experience with data integration, ETL/ELT pipelines, streaming technologies, data lakehouse architectures, Iceberg, Delta, and Parquet.

Nice to have

• Master’s degree in computer science, engineering, mathematics, or a related field.

Culture & Benefits

• Work in an environment focused on impact, innovation, and collaboration.
• Contribute to a rapidly growing organization scaling its engineering and solution engineering teams.
• Build expertise across evolving data technologies, vendors, and enterprise use cases.