Solutions Architect - Financial Services (Hunter)
About The Position
As a Solutions Architect, you will lead technical strategy for Financial Services customers, own architecture discussions, drive platform adoption, and serve as a trusted advisor to customer technical leads and architects. You will combine technical expertise with strategic thinking to position Databricks as the foundation of customers’ data and AI strategies, while developing a technical specialization and becoming a go-to resource within your team. The role covers the end-to-end technical customer journey, from discovery and solution design through production deployment and consumption growth. You will design scalable, production-grade solutions across data engineering, ML/AI, and real-time analytics; demonstrate Databricks’ differentiation in competitive situations; coordinate internal and partner resources; and provide structured customer and competitive feedback to influence product direction.
Requirements
- At least 6 years in solutions architecture, data engineering, technical pre-sales, or a senior hands-on technical role.
- Strong coding proficiency in Python and SQL, including the ability to demonstrate live coding, debugging, and solution building.
- Deep expertise in distributed data systems architecture, including scalable pipelines, streaming architectures, lakehouse patterns, and cloud-native data platforms.
- Proficiency with the Databricks Platform, or demonstrated ability to achieve proficiency rapidly, with a developing technical specialization in an area such as real-time/streaming, ML/AI, data governance, or migrations.
- Proven ability to lead architecture discussions with senior technical stakeholders, including whiteboarding, design reviews, and trade-off analysis.
- Experience with production deployments on public cloud (AWS, Azure, or GCP), including infrastructure, security, and governance considerations.
- Track record of driving platform adoption and consumption growth within accounts.
- Excellent communication skills and ability to translate complex architectures into business value for technical and executive audiences.
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a quantitative discipline, or equivalent experience.
Nice To Haves
- Databricks certifications in Data Engineer, ML, or Platform.
- Experience with competitive platforms such as Snowflake, AWS native services, or Azure Synapse.
- Background in a data/AI company or cloud provider.
- Industry domain expertise, such as Financial Services, Healthcare, Retail, or Media.
Responsibilities
- Own end-to-end technical strategy for accounts, from initial discovery through production deployment and consumption growth.
- Lead complex architecture discussions and design scalable, production-grade solutions spanning data engineering, ML/AI, and real-time analytics.
- Serve as a trusted technical advisor to customer architects, engineering leads, and Directors.
- Drive technical wins in competitive scenarios by demonstrating Databricks’ differentiation through custom-built solutions.
- Develop and declare an emerging technical specialization (archetype), becoming a go-to resource for the team in that domain.
- Orchestrate cross-functional resources, including DSAs, SSAs, and Partners, to deliver comprehensive solutions for complex customer needs.
- Provide structured feedback on customer requirements and competitive gaps to influence product direction.
Benefits
- The total compensation package may include eligibility for an annual performance bonus and equity.
- Databricks offers comprehensive benefits and perks; region-specific details are available through the company’s benefits information.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
