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SnowflakeSnowflakeNew York, NY

Solution Engineer - Data Engineering Specialist (FSI)

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.

189k – 248k
On-site10+ YOESales Engineering

About the role

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

Skills

SQLPythonpandasSparkPysparkHadoopHiveApache NifiMatillionFivetranQlikInformaticaKafkaFlinkSpark Streaming
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