Jobs · Engineering · New York

Sr. Solutions Architect - Financial Services (Banking and Payments)

Databricks · New York, United States · Yesterday
Engineering$219k–$301k/yrFull-time

As a Sr. Solutions Architect, you are an expert-level technical leader responsible for the organization's most complex customer engagements. You drive consumption strategy, own executive-level relationships, and serve as the definitive technical authority for your accounts. You have declared your archetype—a recognized technical specialization that makes you a force multiplier across your team and region. You operate at the intersection of deep technical expertise, strategic account planning, and executive influence.

Responsibilities

  • Drive the technical and consumption strategy for the organization's most complex customer engagements, directly influencing platform adoption and revenue growth.
  • Own senior-level technical relationships — serving as a trusted advisor on enterprise data and AI strategy.
  • Lead the most complex architecture engagements: multi-workload platforms, enterprise-wide migrations, real-time systems, and AI/ML at scale.
  • Operate as an Expert on the Databricks Platform with a declared archetype — actively mentoring others and driving horizontal impact across your team.
  • Develop and execute competitive strategies for your customers, positioning Databricks against incumbent and emerging platforms.
  • Orchestrate cross-functional teams (DSAs, SSAs, Partners, Product) to deliver enterprise-grade solutions.
  • Coach and develop junior SAs (L3–L5) on technical depth, customer engagement, and use case prioritization.
  • Contribute to Field Engineering thought leadership through customer-facing content, workshops, and community engagement.

Requirements

  • 8+ years in solutions architecture, principal engineering, technical pre-sales leadership, or a senior customer-facing technical role.
  • Expert-level coding proficiency — Python, SQL, and ideally Spark/PySpark. You will complete a live coding assessment and a platform build during the interview.
  • Deep expertise in enterprise data architecture: distributed systems at scale, streaming/real-time, lakehouse design

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