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Principal Solutions Architect - Data Engineering

Snowflake Inc.· Professional Services
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US-NY-New York$196k - $257.2kFull-timePosted 1mo ago

About the role

Strategic role to help customers modernize and expand their use of the Snowflake AI Data Cloud, leading agentic data engineering initiatives and delivering Snowflake-centric data architectures and pipelines from ideation to production.

Responsibilities

  • Be a technical expert on all aspects of Snowflake as it applies to data engineering to provide customers with best practices given Snowflake's technology stack.
  • Work with customers to understand their data engineering and platform modernization goals, discover key requirements, and architect a Snowflake-centric solution to be delivered by Services Delivery.
  • Understand how to build and deploy data pipelines with Snowflake features within the Snowflake ecosystem based on customer requirements.
  • Pioneer agentic data engineering practices. Use AI coding agents and Snowflake's AI capabilities to speed up pipeline development, code conversion and migration, testing, documentation, and day-to-day operations. Turn these approaches into repeatable delivery patterns and accelerators.
  • Work hands-on where needed in SQL, Python, Snowpark, dbt, and agentic development tools to build POCs and reference implementations that show engineering techniques and best practices on Snowflake.
  • Follow best practices, including ensuring knowledge transfer so that customers are properly enabled and are able to extend the capabilities of Snowflake on their own.
  • Maintain a deep understanding of competing and complementary technologies and vendors in data engineering and in AI-assisted development, and know how to position Snowflake against them.
  • Guide customers through their specific technical challenges, such as complex migrations, performance tuning, and cost optimization.
  • Support other members of the Services Delivery team as they develop their expertise.
  • Work with Product Management, Engineering, and Marketing to keep improving Snowflake's products and marketing. Feed real-world delivery insights back into the roadmap for data engineering and agentic features.

Qualifications

  • Minimum 5 years experience working with customers in a pre-sales or post-sales technical role.
  • Outstanding skills presenting to both technical and executive audiences, whether impromptu on a whiteboard or using presentations and demos.
  • Thorough understanding of the complete data engineering lifecycle, including data ingestion, transformation, orchestration, data modeling, and data quality.
  • Thorough understanding of modern data architecture patterns, including batch and streaming pipelines, ELT, lakehouse and open table formats (Apache Iceberg), and data warehouse migration and modernization.
  • Strong understanding of DataOps, along with the technologies and methods for deploying, testing, monitoring, and governing data pipelines (CI/CD, observability, performance tuning, and cost optimization).
  • Hands-on experience applying AI coding agents and agentic workflows to accelerate data engineering work such as pipeline development, code conversion, testing, and operations.
  • Experience and understanding of at least one public cloud platform (AWS, Azure or GCP).
  • Experience with at least one data platform or integration technology such as Databricks, AWS Glue/EMR, Azure Data Factory/Synapse, GCP BigQuery/Dataflow, Informatica, Fivetran, etc.
  • Hands-on scripting experience with SQL and at least one of the following: Python, Java or Scala.
  • Experience with tools and frameworks such as dbt, Apache Spark/PySpark, Apache Airflow, Kafka, Pandas, or similar.
  • University degree in computer science, engineering, data science, mathematics or related fields, or equivalent experience.

Skills

Required:Data engineering lifecycleSnowflake and data architecturesAgentic data engineering / AI coding agents
Last updated Oct 8, 2026. Interested? Apply on the company site.

About Snowflake Inc.

The Data Platform Built for Data Teams.

Snowflake powers AI, data engineering, applications, and analytics on a trusted, scalable AI Data Cloud—eliminating silos and accelerating innovation.

AIData CloudData EngineeringAnalyticsApplications & Collaboration
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