Solutions Architect

The Impact You Will Have

Own the end-to-end technical strategy for your accounts, from initial discovery through production deployment and consumption growth
Lead complex architecture discussions — designing 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 your team in that domain
Orchestrate cross-functional resources (DSAs, SSAs, Partners) to deliver comprehensive solutions for complex customer needs
Influence product direction by providing structured feedback on customer requirements and competitive gaps

What We Look For

6+ years in solutions architecture, data engineering, technical pre-sales, or a senior hands-on technical role
Strong coding proficiency in Python and SQL — you must demonstrate live coding, debugging, and solution-building skills
Deep expertise in distributed data systems architecture: designing scalable pipelines, streaming architectures, lakehouse patterns, and cloud-native data platforms
Proficient on the Databricks Platform (or demonstrated ability to achieve proficiency rapidly) with a developing technical specialization in one area (e.g., real-time/streaming, ML/AI, data governance, migrations)
Proven ability to lead architecture discussions with senior technical stakeholders — 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 — able to translate complex architectures into business value for both technical and executive audiences
Ability to travel to customers 30% of the time
Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline (or equivalent experience)

Nice to Have:

Databricks certifications (Data Engineer, ML, Platform)
Experience with competitive platforms (Snowflake, AWS native services, Azure Synapse) — understanding the landscape you'll position against
Background in a data/AI company or cloud provider
Industry domain expertise (Financial Services, Healthcare, Retail, Media, etc.)