Senior Solution Engineer

As a Senior Solution Engineer at Snowflake, you will partner closely with Sales, Product, Engineering, and Marketing to drive customer success across the Financial Services industry. You will act as a trusted technical advisor, translating complex business challenges into scalable, secure, and high-performing data platform solutions on Snowflake.

This role requires a blend of deep technical expertise, industry knowledge, and strong customer engagement skills. You will lead technical discovery, architect solutions, deliver compelling demonstrations, and guide customers through proof-of-concepts and production adoption.

A strong understanding of the Singapore regulatory landscape (e.g., MAS guidelines, data residency, cloud security requirements) is essential.

RESPONSIBILITIES:

• Present Snowflake technology and vision to executives and technical contributors at prospects and customers

• 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

• Maintain a deep understanding of competitive and complementary technologies and vendors and how to position Snowflake in relation to them

• Collaborate with Product, Engineering, and Marketing to provide FSI-specific feedback, influence roadmap, and create reusable assets (reference architectures, demo patterns, best practices)

• Be an advocate and develop mutual trust with the technical audience on the customer side

MINIMUM REQUIREMENTS:

• Extensive working experience in customer facing solution engineering role

• Strong competency on modern data stacks, ETL/ELT, data warehouse/lake, data science , Gen AIand Data Apps

• Excellent ability to present to both technical and executive audiences, whether through impromptu whiteboarding or structured presentations and demos.

• Hands-on expertise with SQL & Spark

STRONGLY DESIRED:

• Experience with large-scale data platforms (e.g., Teradata, Netezza, Exadata, Greenplum, Hadoop)

• Programming/scripting experience (e.g., Python, Java, Spark)

• Experience selling or supporting enterprise data/analytics platforms

• Strong stakeholder management and value-based selling skills

• Degree in Computer Science, Engineering, Mathematics, or related field skills

• Identifying key stakeholders, winning value propositions, and compelling events

ADDED BONUS FOR:

• Hands-on experience with Lakehouse architectures

• Exposure to Data Science / AI / ML / Generative AI workloads

• Familiarity with BI tools (e.g., Tableau, Power BI)

• Cloud platform experience: AWS, Azure, or GCP

• Relevant services (e.g., S3, Glue, SageMaker, Azure Data Factory, etc.)

• Experience with OLAP data modeling and enterprise data architecture

• Background in Financial Services (either as a practitioner or vendor)

• Experience selling enterprise SaaS solutions