# Solution Engineer - Data Engineering Specialist (FSI)

**Company:** [Snowflake](https://hotfix.jobs/companies/snowflake)
**Location:** New York, NY
**Role:** Sales Engineering
**Salary:** $189k – $248k/yr
**Experience:** 10+ years
**Skills:** SQL, Python, pandas, Spark, Pyspark, Hadoop, Hive, Apache Nifi, Matillion, Fivetran, Qlik, Informatica, Kafka, Flink, Spark Streaming
**Posted:** 2026-04-21

> Provides technical leadership in designing Snowflake Cloud Data Platform architectures for Financial Services clients, supporting sales with demos, POCs, and value demonstrations. Requires 10+ years data engineering experience and 5+ years pre-sales expertise.

## Job Description

## Responsibilities

- Apply 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

- 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.)
- Proven experience working with Financial Services customers
- 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 (e.g., Data Lake, Data Mesh, Data Fabric)
- Hands-on development experience with **SQL**, **Python**, **Pandas**, **Spark**, **PySpark**, **Hadoop**, **Hive** and 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 (**Kafka**, **Flink**, **Spark Streaming**, **Kinesis**) and real-time or near real-time use cases (e.g., CDC)
- Experience designing interoperable data lakehouse architectures and working with **Iceberg**, **Delta**, and **Parquet**
- Strong architectural expertise in data engineering to confidently present and demo to business executives and technical audiences
- Bachelor’s Degree required; Master’s Degree in computer science, engineering, mathematics or related fields preferred

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