Principal Data Platform Architect – Data Engineering, Applied Field Engineering

Snowflake

Principal Data Platform Architect working with customers to implement Snowflake technology for data solutions. Leading technical engagements and demonstrations to drive enterprise data architecture success.

Posted 5/21/2026full-timeRemote • Colorado • 🇺🇸 United StatesLead💰 $189,000 - $248,062 per yearWebsite

Tech Stack

Tools & technologies

ApacheCloudETLHadoopInformaticaKafkaMatillionPandasPySparkPythonSparkSQL

About the role

Key responsibilities & impact

Apply your multi-cloud data architecture expertise while presenting Snowflake technology and vision to executives and technical contributors at strategic prospects, customers, and partners
Work hands-on with prospects and customers to demonstrate and communicate the value of Snowflake technology throughout the sales cycle, from demo to proof of concept to design and implementation
Immerse yourself in the ever-evolving industry, maintaining a deep understanding of competitive and complementary technologies and vendors and how to position Snowflake in relation to them
Collaborate with Product Management, Engineering, and Marketing to continuously improve Snowflake’s products and marketing

Requirements

What you’ll need

10+ years of architecture and data engineering experience within the Enterprise Data space
5+ years experience within a pre-sales environment (Sales Engineer, Solutions Engineer, Solutions Architect, etc…)
Outstanding presentation skills to both technical and executive audiences, whether impromptu on a whiteboard or using presentations and demos.
Ability to connect a customer’s specific business problems and Snowflake’s solutions
Ability to do deep discovery of customer’s architecture framework and connect those with Snowflake Data Architecture.
Broad range of experience within large-scale Database and/or Data Warehouse technology, ETL, analytics and cloud technologies. For example, Data Lake, Data Mesh, Data Fabric
Hands on Development experience with technologies such as SQL, Python, Pandas, Spark, PySpark, Hadoop, Hive and any other Big data technologies
Deep understanding of data integration services and tools for building ETL and ELT data pipelines such as Apache NiFi, Matillion, Fivetran, Qlik, or Informatica.
Familiarity with streaming technologies (ex. Kafka, Flink, Spark Streaming, Kinesis) and real-time or near real time use cases (ex. CDC)
Experience designing interoperable data lakehouse architectures and experience working with Iceberg, Delta, and Parquet
Strong architectural expertise in data engineering to confidently present and demo to business executives and technical audiences, and effectively handle any impromptu questions
Bachelor’s Degree required, Masters Degree in computer science, engineering, mathematics or related fields, or equivalent experience *preferred*

Benefits

Comp & perks

Health insurance
Flexible work arrangements

ATS Keywords

✓ Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data architecturedata engineeringSQLPythonPandasSparkPySparkHadoopHiveETL

Soft Skills

presentation skillscommunicationcollaborationproblem-solvingcustomer discoverytechnical audience engagementexecutive audience engagementimprovisationstrategic thinkingadaptability