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Snowflake is seeking a Senior Solutions Engineer to own the full technical relationship with a single strategically important global financial services customer. This is a named-account role focused on a tier-1 financial institution across capital markets, banking, insurance, or asset management. You will serve as the trusted technical advisor to C-suite executives (CTO, CDO, engineering leadership), driving use case expansion across business units and acting as the primary internal advocate within Snowflake.
Key responsibilities include owning the end-to-end technical relationship from discovery through proof of concept, technical close, and ongoing expansion. You will build and deliver compelling demonstrations, solution architectures, and executive presentations that connect Snowflake's platform capabilities to the customer's data and AI priorities. You will design and lead proof of concept engagements covering risk analytics, regulatory data platforms, real-time fraud detection, customer intelligence, and AI/ML workloads in financial services environments.
As a subject matter expert on financial services data architecture, you will translate complex regulatory and technical requirements into production-ready Snowflake solutions. You will partner closely with the Account Executive and Snowflake leadership to co-develop joint success plans and ensure technical alignment across opportunities. You will coordinate across Product, Professional Services, Support, and Engineering to resolve blockers and accelerate adoption. Additionally, you will mentor junior Solution Engineers, elevating the technical standard of the global accounts practice.
Required qualifications include 8+ years in pre-sales solution engineering, technical consulting, or data engineering in enterprise B2B technology, with significant financial services exposure. You need deep understanding of FSI data use cases including risk management, regulatory reporting (Basel, MiFID II, GDPR), market data, fraud analytics, and AI/ML for credit and customer intelligence. Strong hands-on expertise with cloud data platforms (ideally Snowflake) and the ability to architect and demo enterprise-grade solutions live are essential. Proficiency in SQL, Python, and data engineering tools (dbt, Spark, Kafka) commonly used in FSI is required. Excellent executive communication skills and a track record of leading complex technical evaluations and winning competitive PoCs are critical. Experience using AI and LLM-based tools in technical workflows is expected.
Bonus qualifications include direct experience with capital markets firms, tier-1 banks, insurers, or global asset managers; hands-on Snowflake experience including Cortex AI, data sharing, Snowpark, and Native Apps; familiarity with financial services cloud migration patterns and legacy platforms; experience with real-time data architectures and streaming ingestion in regulated environments; and background in data mesh, data product design, or enterprise data governance frameworks.
