Solutions Architect - Financial Services (Hunter)

About the role

Databricks is hiring a Solutions Architect for its Financial Services practice. You will own the technical strategy for your customers, from discovery through production deployment, and act as a trusted advisor to their technical leads and architects. You will develop a technical specialization (archetype) and become a go-to resource for your team in that domain.

Key responsibilities

• Own the end-to-end technical strategy for your accounts, from initial discovery through production deployment and consumption growth.
• Lead complex architecture discussions covering data engineering, ML/AI and real-time analytics, designing scalable, production-grade solutions.
• Serve as a trusted technical advisor to customer architects, engineering leads and Directors.
• Win competitive scenarios by showing Databricks' differentiation through custom-built solutions.
• Develop and declare an emerging technical specialization.
• Orchestrate DSAs, SSAs and partners to deliver comprehensive solutions for complex customer needs.
• Influence product direction with structured feedback on customer requirements and competitive gaps.

Required profile

• 6+ years in solutions architecture, data engineering, technical pre-sales or a senior hands-on technical role.
• Proven ability to lead architecture discussions with senior technical stakeholders, including whiteboarding, design reviews and trade-off analysis.
• Track record of driving platform adoption and consumption growth within accounts.
• Bachelor's or Master's degree in Computer Science, Engineering or a quantitative discipline (or equivalent experience).

Required skills

• Strong coding in Python and SQL, with live coding, debugging and solution-building demonstrated.
• Deep expertise in distributed data systems: scalable pipelines, streaming architectures, lakehouse patterns and cloud-native data platforms.
• Proficiency on the Databricks Platform, with a developing specialization in one area (e.g. real-time/streaming, ML/AI, data governance, migrations).
• Production deployments on public cloud (AWS, Azure or GCP), including infrastructure, security and governance.
• Nice to have: Databricks certifications (Data Engineer, ML, Platform); experience with Snowflake, AWS native services or Azure Synapse; background in a data/AI company or cloud provider; industry domain expertise (Financial Services, Healthcare, Retail, Media).

The interview process runs from recruiter screen through a live coding assessment, presentation and reference check. The stated pay range is $180,000-$247,500 USD, with possible annual performance bonus and equity.