Lead the technical strategy for customers as a Solutions Architect at Databricks, focusing on data and AI solutions.
Posted by employer 1 week ago
First seen on Joblaze 1 week ago
Last verified on the company career page 19 hours ago
Not disclosed in this posting: compensation, work arrangement, visa sponsorship.
Joblaze summary
In the role of Solutions Architect at Databricks, the individual will lead the technical strategy for clients, guiding architecture discussions and driving platform adoption. Key skills include strong coding abilities in Python and SQL, along with expertise in distributed data systems and cloud-native platforms. This position is suited for professionals with over six years of experience in solutions architecture or related fields, particularly those who can engage effectively with senior technical stakeholders. Databricks emphasizes a collaborative approach, leveraging cross-functional resources to meet complex customer needs.
Quick facts
- How much experience is required?
- At least 6 years of relevant experience for this Solutions Architect role.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: AWS, Azure, Databricks, GCP, Python, SQL.
- What seniority level is this role?
- Databricks targets senior candidates for this position.
- Is this full-time or contract?
- Full-time for this Solutions Architect role at Databricks.
From the original posting
Req ID: FEQ427R18
Location London, UK
The Role
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
- 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
Standard company text repeated across Databricks's postings is omitted here.