Sr. Solutions Architect - Financial Services (Asset and Wealth Management)
Databricks Mosaic · Chicago, Illinois; Massachusetts; New Jersey; New York · New Jersey
CHECKED 15H AGO
Infrastructureonsitesenior$219k–$301k
At a glance
Highlights
- Drive consumption strategy for the most complex customer engagements.
- Lead multi-workload platforms, enterprise migrations and AI at scale.
- Serve as trusted advisor to directors, VPs and C-level on data strategy.
What they offer
- Annual performance bonus
- Equity
- Comprehensive benefits and perks
Ideal candidate
A senior customer-obsessed technical leader who thrives on complex enterprise challenges and executive influence. You love connecting architecture to business outcomes and mentoring others in financial services.
Requirements
- 8+ years in solutions architecture, principal engineering, technical pre-sales leadership, or senior customer-facing technical role
- Expert-level coding proficiency in Python, SQL, and ideally Spark/PySpark
- Deep expertise in enterprise data architecture: distributed systems, streaming, lakehouse design, governance, cloud-native platforms
- Expert-level Databricks Platform knowledge or equivalent depth in competing platforms
- Declared technical specialization such as real-time architectures, ML/AI platforms, governance, migrations, or industry solutions
- Proven track record driving consumption growth and platform adoption in large accounts
- Executive presence with ability to influence Directors, VPs, and C-level stakeholders
- Experience leading competitive displacements and complex enterprise evaluations
- Bachelor's or Master's in Computer Science, Engineering, or quantitative discipline or equivalent experience
- hiring process
- Recruiter Screen → Hiring Manager Screen → Design and Architecture Interview → Live Coding Assessment → Build, Demo, Pitch! Presentation → Reference Check
Lab profile
About Databricks Mosaic
Builds unified data analytics and AI platform to productionize AI applications.
What they build
- Databricks platform
- Unified Data Analytics and AI
- AI platform
Known for
- Forward-deployed AI engineering
- Productionizing first-of-kind AI applications
- Customer platform adoption and scale
- Cross-functional engineering and product collaboration