Solution Engineer – Data Engineering Specialist

🕒 il y a 24 jours

🇺🇸 États-Unis – Télétravail

💵 $189 000 - $248 062 / an

⏰ Temps Plein

🟠 Senior

🔴 Expert

💻 Ingénieur Solutions

🦅 Parrain de Visa H1B

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Snowflake

Site WebLinkedInTous les Emplois

5001 - 10000 employés

Fondée en 2012

☁️ SaaS

Cloud Computing • Data Analytics • SaaS

Snowflake est une entreprise de stockage de données basée sur le cloud qui offre une plateforme innovante pour le stockage, le traitement et l'analyse de données. Elle permet aux organisations de gérer efficacement de grands volumes de données, facilitant ainsi la génération d'insights et l'intelligence économique. L'architecture de Snowflake prend en charge diverses charges de travail de données, ce qui en fait une solution polyvalente pour les entreprises cherchant à exploiter leurs données pour prendre des décisions stratégiques.

Description

• 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 • Immerse yourself in the ever-evolving industry, maintaining a deep understanding of competitive and complementary technologies and vendors • Collaborate with Product Management, Engineering, and Marketing to continuously improve Snowflake’s products and marketing

🎯 Exigences

• 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 • 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 • Hands on Development experience with technologies such as 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 • Familiarity with streaming technologies (ex. Kafka, Flink, Spark Streaming, Kinesis) • 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

🏖️ Avantages

• Health insurance • 401(k) • Professional development opportunities