Solutions Architect (Digital Native Business)
About this role
Databricks builds a unified data and AI platform relied on by organizations worldwide to scale data and AI applications, analytics, and agents. The London-based team requires a Solutions Architect to lead technical strategy, drive platform adoption, and act as a trusted advisor to customer technical leads and architects throughout the account lifecycle. Daily responsibilities involve designing scalable solutions spanning data engineering, machine learning, real-time analytics, and cloud environments while developing a distinct technical specialisation.
Candidates applying for this position should bring extensive technical experience in pre-sales, data engineering, or solutions architecture, along with strong coding skills in Python and SQL. Success in the role requires an ability to navigate competitive scenarios, orchestrate cross-functional partners, and translate complex distributed data systems into business value for senior technical stakeholders.
What you will do
- Manage the end-to-end technical strategy for assigned accounts from the initial discovery phase through to production deployment and consumption growth.
- Lead complex architecture discussions focused on designing scalable and production-grade solutions across data engineering, artificial intelligence, machine learning, and real-time analytics.
- Act as a trusted technical advisor to customer engineering leads, architects, and directors.
- Secure technical wins in competitive environments by demonstrating platform differentiation through custom-built solutions.
- Develop and declare an emerging technical specialisation or archetype to serve as a domain resource for the team.
- Coordinate cross-functional resources including specialist architects and partners to deliver comprehensive solutions for customer needs.
- Provide structured feedback on customer requirements and competitive gaps to influence product direction.
What you need
- Bring at least six years of professional experience in solutions architecture, technical pre-sales, data engineering, or a senior hands-on technical capacity.
- Demonstrate strong coding proficiency in Python and SQL, including the ability to perform live coding, debugging, and solution building.
- Possess deep expertise in distributed data systems architecture such as scalable pipelines, streaming architectures, lakehouse patterns, and cloud-native data platforms.
- Show proficiency on the Databricks Platform or a demonstrated ability to learn it rapidly while developing a technical specialisation in areas like streaming, governance, migrations, or machine learning.
- Have a proven track record of leading architecture discussions with senior technical stakeholders through whiteboarding, design reviews, and trade-off analysis.
- Understand production deployments on public cloud providers like AWS, Azure, or GCP, covering infrastructure, security, and governance.
- Hold a Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline, or possess equivalent practical experience.
Nice to have
- Databricks certifications such as Data Engineer, Machine Learning, or Platform
- Experience with competitive platforms including Snowflake, AWS native services, or Azure Synapse
- Background working at a data and AI company or a cloud provider
- Industry domain expertise in sectors like Financial Services, Healthcare, Retail, or Media
Skills and tech stack
Questions candidates ask
What does the interview process look like?
The evaluation process starts with a recruiter screen followed by a hiring manager screen. Candidates then move through a design and architecture interview, a live coding assessment, and a final build, demo, pitch presentation alongside a reference check.
What kind of technical background is required?
Applicants need at least six years of experience in solutions architecture, data engineering, technical pre-sales, or a senior hands-on technical role. Strong coding proficiency in Python and SQL is mandatory, alongside deep expertise in distributed data systems architecture.
What will I actually be working on day-to-day?
You will own the technical strategy for customer accounts, lead architecture discussions, and design production-grade solutions spanning data engineering, machine learning, and real-time analytics. You will also develop a technical specialisation and help drive platform adoption.