Role at a glance
- Salary
- Not Disclosed
- Location
- United Kingdom - London
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 4+ years in data engineering, solutions architecture, technical pre-sales, or a hands-on consulting role
- Education
- Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline (or equivalent experience)
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Role Summary
The Sr. Solutions Engineer leads technical customer engagements for the Databricks Platform, combining coding, architecture, demonstrations, and customer-facing work to drive platform adoption. The role partners with Account Executives and customer technical teams across data engineering, analytics, and machine learning workloads.
What You'll Do
- Lead technical discovery and solution design for customer workloads spanning data engineering, analytics, and machine learning
- Build and deliver proofs-of-concept and live demonstrations on the Databricks Platform
- Own frontline technical relationships with customer engineers, data teams, and technical leads
- Develop account-level technical strategies in partnership with the Account Executive
- Articulate Databricks differentiation through hands-on demonstrations in competitive situations
- Contribute reusable technical assets, including notebooks, solution accelerators, and reference architectures
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Requires 4+ years of relevant experience; proficiency in Python and SQL; hands-on experience with at least one public cloud platform; working knowledge of distributed data systems; experience leading technical customer conversations; familiarity with data engineering, data science/ML, or SQL analytics; strong presentation and demo skills; and a bachelor's or master's degree in Computer Science, Engineering, or a quantitative discipline or equivalent experience.
Required
- 4+ years in data engineering, solutions architecture, technical pre-sales, or a hands-on consulting role
- Proficient in Python and SQL
- Hands-on experience designing and implementing data solutions on at least one public cloud platform (AWS, Azure, or GCP)
- Working knowledge of distributed data systems: Apache Spark™, Delta Lake, or equivalent (Hadoop, Kafka, Flink)
- Experience leading technical customer conversations — discovery, whiteboarding, architecture reviews
- Familiarity with one or more: data engineering (ETL/ELT, medallion architecture, streaming), data science/ML (model training, MLOps), or...
- Strong presentation and demo skills
- Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline (or equivalent experience)
Preferred
- Databricks certification or experience with the Databricks Platform
- Experience with Unity Catalog, Lakeflow Spark Declarative Pipelines, or MLflow
- Background at a data/AI company, cloud provider, or technical consulting firm
Original job description
Content provided by the employer
Original job description
Content provided by the employer
FEQ327R417
The Role
As a Sr. Solutions Engineer, you will independently lead technical engagements for customers, owning discovery, solution design, and platform demonstrations. You are a builder who can code, architect, and present—combining technical depth with customer-facing skills to drive Databricks adoption. You will own frontline customer relationships and work with your Account Executive to develop technical strategies that expand platform usage.
The Impact You Will Have
- Independently lead technical discovery and solution design for customer workloads spanning data engineering, analytics, and machine learning
- Build and deliver compelling proofs-of-concept and live demos on the Databricks Platform that drive technical wins
- Own frontline technical relationships with customer engineers, data teams, and technical leads
- Develop account-level technical strategies in partnership with your Account Executive to grow platform consumption
- Navigate competitive landscapes by articulating Databricks differentiation through hands-on demonstrations
- Contribute reusable technical assets (notebooks, solution accelerators, reference architectures) to the broader SA community
What We Look For
- 4+ years in data engineering, solutions architecture, technical pre-sales, or a hands-on consulting role
- Proficient in Python and SQL with demonstrated ability to debug, optimize, and write production-quality code — live coding is a required interview stage
- Hands-on experience designing and implementing data solutions on at least one public cloud platform (AWS, Azure, or GCP)
- Working knowledge of distributed data systems: Apache Spark™, Delta Lake, or equivalent (Hadoop, Kafka, Flink)
- Experience leading technical customer conversations — discovery, whiteboarding, architecture reviews
- Familiarity with one or more: data engineering (ETL/ELT, medallion architecture, streaming), data science/ML (model training, MLOps), or SQL analytics
- Strong presentation and demo skills — you will build and present a live solution during the interview
- Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline (or equivalent experience)
Nice to Have:
- Databricks certification or experience with the Databricks Platform
- Experience with Unity Catalog, Lakeflow Spark Declarative Pipelines, or MLflow
- Background at a data/AI company, cloud provider, or technical consulting firm
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.