Databricks

Builds cloud software for data analysis and AI

Senior Solutions Architect - Banking, Financial Services

Pre-Sales Solution EngineeringConfirmed live in the last 24 hours

Full-timeLondon, UKNo salary listedIn-person

About the Job

Requirements

At least 8 years of experience in solutions architecture, principal engineering, technical pre-sales leadership, or a senior customer-facing technical role.
Expert-level coding proficiency in Python and SQL; Spark/PySpark is ideal. The interview includes a live coding assessment and a platform build.
Deep expertise in enterprise data architecture, including distributed systems at scale, streaming and real-time systems, lakehouse design patterns, data governance frameworks, and cloud-native platforms.
Expert-level Databricks Platform knowledge, or equivalent depth in competing platforms with demonstrated ability to learn rapidly.
Recognized depth in a declared technical specialization, such as real-time architectures, ML/AI platforms, data governance, large-scale migrations, or industry-specific solutions.
A proven track record of driving consumption growth and platform adoption in large accounts.
Ability to influence Directors, VPs, and C-level stakeholders on long-term data and AI strategy.
Experience leading competitive displacements and complex enterprise evaluations.
Strategic thinking that connects technical architecture decisions to business outcomes and revenue impact.
A bachelor's or master's degree in Computer Science, Engineering, or a quantitative discipline, or equivalent experience; advanced degrees are valued.

Responsibilities

Drive technical and consumption strategy for complex customer engagements, influencing platform adoption and revenue growth.
Own senior-level technical relationships and advise customers on enterprise data and AI strategy.
Lead complex architecture engagements, including multi-workload platforms, enterprise-wide migrations, real-time systems, and AI/ML at scale.
Serve as a Databricks Platform expert with a declared archetype, mentoring others and driving horizontal impact across the team.
Develop and execute competitive strategies for customers, positioning Databricks against incumbent and emerging platforms.
Orchestrate cross-functional teams, including DSAs, SSAs, partners, and product teams, to deliver enterprise-grade solutions.
Coach and develop junior SAs (L3–L5) in technical depth, customer engagement, and use case prioritization.
Contribute to Field Engineering thought leadership through customer-facing content, workshops, and community engagement.

Desired Qualifications

Databricks certifications.
Prior experience at Databricks, Snowflake, AWS, Google, Microsoft, or a top-tier data/AI company.
Published thought leadership, such as blogs, conference talks, or open-source contributions.
Industry vertical expertise with executive-level domain credibility.

JOB ID: FEQ427R344
Location: London, United Kingdom
Industry: Banking, Financial Services -Industry (UK&I Enterprise)
Recruiter: Dina Hussain

The Role

As a Sr. Solutions Architect, you are an expert-level technical leader responsible for the organization's most complex customer engagements. You drive consumption strategy, own executive-level relationships, and serve as the definitive technical authority for your accounts. You have declared your archetype—a recognized technical specialization that makes you a force multiplier across your team and region. You operate at the intersection of deep technical expertise, strategic account planning, and executive influence.

The Impact You Will Have

Drive the technical and consumption strategy for the organization's most complex customer engagements, directly influencing platform adoption and revenue growth.
Own senior-level technical relationships — serving as a trusted advisor on enterprise data and AI strategy
Lead the most complex architecture engagements: multi-workload platforms, enterprise-wide migrations, real-time systems, and AI/ML at scale
Operate as an Expert on the Databricks Platform with a declared archetype — actively mentoring others and driving horizontal impact across your team
Develop and execute competitive strategies for your customers, positioning Databricks against incumbent and emerging platforms
Orchestrate cross-functional teams (DSAs, SSAs, Partners, Product) to deliver enterprise-grade solutions
Coach and develop junior SAs (L3–L5) on technical depth, customer engagement, and use case prioritization
Contribute to Field Engineering thought leadership through customer-facing content, workshops, and community engagement

What We Look For

8+ years in solutions architecture, principal engineering, technical pre-sales leadership, or a senior customer-facing technical role
Expert-level coding proficiency — Python, SQL, and ideally Spark/PySpark. You will complete a live coding assessment and a platform build during the interview
Deep expertise in enterprise data architecture: distributed systems at scale, streaming/real-time, lakehouse design patterns, data governance frameworks, and cloud-native platforms
Expert-level Databricks Platform knowledge (or equivalent depth in competing platforms with demonstrated rapid learning ability)
Declared technical specialization with recognized depth — e.g., real-time architectures, ML/AI platforms, data governance, large-scale migrations, or industry-specific solutions
Proven track record of driving consumption growth and platform adoption in large accounts
Executive presence — ability to influence Directors, VPs, and C-level stakeholders on long-term data and AI strategy
Experience leading competitive displacements and complex enterprise evaluations
Strong strategic thinking — connecting technical architecture decisions to business outcomes and revenue impact
Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline (or equivalent experience); advanced degrees are valued

Nice to Have:

Databricks certifications
Prior experience at Databricks, Snowflake, AWS, Google, Microsoft, or a top-tier data/AI company
Published thought leadership (blogs, conference talks, open source contributions)
Industry vertical expertise with executive-level domain credibility

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

Builds cloud software for data analysis and AI

Databricks builds cloud software that businesses use to organize data, analyze it, and develop AI applications. Its lakehouse architecture brings the flexible storage of a data lake together with the querying and management tools of a data warehouse. Data engineers prepare and update datasets, analysts build reports, and developers train models or create applications in a shared workspace with controls over who can use the data. The platform runs on Amazon, Microsoft, and Google clouds, and customers pay for computing usage or commit to longer contracts for discounted rates. Databricks was founded in 2013 and is headquartered in San Francisco, California.

Company size: 10,001+
Company stage: Late Stage VC
Total funding: $32.1B
Headquarters: San Francisco, CA
Founded: 2013

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