Role at a glance
- Salary
- Not Disclosed
- Location
- United States Remote - US - California
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 6+ years in solutions architecture, data engineering, technical pre-sales, or a senior hands-on technical role
- Education
- Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline (or equivalent experience)
Spotted an issue?
We’ll check it against the original posting.
Role Summary
The Solutions Architect leads technical strategy for customer accounts and advises customer technical leads, architects, engineering leads, and Directors. The role designs data and AI solutions on the Databricks Platform, supports platform adoption and consumption growth, and develops a technical specialization to support complex customer needs.
What You'll Do
- Own the end-to-end technical strategy for accounts from initial discovery through production deployment and consumption growth
- Lead architecture discussions spanning data engineering, ML/AI, and real-time analytics
- Serve as a trusted technical advisor to customer architects, engineering leads, and Directors
- Demonstrate Databricks differentiation through custom-built solutions in competitive scenarios
- Orchestrate DSAs, SSAs, and Partners to deliver comprehensive solutions
- Provide structured feedback on customer requirements and competitive gaps to influence product direction
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
6+ years in solutions architecture, data engineering, technical pre-sales, or a senior hands-on technical role; strong coding proficiency in Python and SQL; expertise in distributed data systems architecture, public-cloud production deployments, and architecture discussions; ability to travel to customers 30% of the time; excellent communication skills.
Required
- Strong coding proficiency in Python and SQL
- Deep expertise in distributed data systems architecture
- Proficient on the Databricks Platform or demonstrated ability to achieve proficiency rapidly
- Experience with production deployments on public cloud (AWS, Azure, or GCP)
- Proven ability to lead architecture discussions with senior technical stakeholders
- Track record of driving platform adoption and consumption growth within accounts
- Ability to travel to customers 30% of the time
Preferred
- Databricks certifications (Data Engineer, ML, Platform)
- Experience with competitive platforms (Snowflake, AWS native services, Azure Synapse)
- Background in a data/AI company or cloud provider
- Industry domain expertise (Financial Services, Healthcare, Retail, Media, etc.)
Original job description
Content provided by the employer
Original job description
Content provided by the employer
FEQ327R394
As a Solutions Architect, you will lead the technical strategy for your customers — owning architecture discussions, driving platform adoption, and serving as a trusted advisor to customer technical leads and architects. You combine deep technical expertise with strategic thinking to position Databricks as the foundation of your customers’ data and AI strategy. You are developing a technical specialization (archetype) and are recognized within your team for depth in a specific domain.
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.)
Interview Process: Recruiter Screen → Hiring Manager Screen → Design and Architecture Interview → Live Coding Assessment → Build, Demo, Pitch! Presentation → Reference Check
About Databricks
Databricks is the Data and AI company. More than 20,000 organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 — rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.
Benefits
At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.
Our Commitment to Diversity and Inclusion
At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.
Compliance
If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.
About the company
Databricks
Large Enterprise
Databricks is a cloud-based data platform that specializes in providing solutions for data engineering, machine learning, and analytics. Founded in 2013 by the original creators of Apache Spark, the company enables organizations to unify data processing and analysis workflows, facilitating collaboration for data professionals. Databricks offers an integrated environment for data scientists, engineers, and business analysts, streamlining the process of building and deploying AI and data-driven applications. With a strong emphasis on simplifying big data management, Databricks helps businesses harness the power of their data to drive innovation and insights.
Databricks is a cloud-based data platform that specializes in providing solutions for data engineering, machine learning, and analytics. Founded in 2013 by the original creators of Apache Spark, the company enables organizations to unify data processing and analysis workflows, facilitating collaboration for data professionals. Databricks offers an integrated environment for data scientists, engineers, and business analysts, streamlining the process of building and deploying AI and data-driven applications. With a strong emphasis on simplifying big data management, Databricks helps businesses harness the power of their data to drive innovation and insights.