Job description

FEQ427R337 While candidates in the listed location(s) are encouraged for this role, candidates in other locations will be considered. At Databricks, our core principles are at the heart of everything we do; creating a culture of proactiveness and a customer-centric mindset guides us to create a unified platform that makes data science and analytics accessible to everyone. We aim to inspire our customers to make informed decisions that push their business forward. We provide a user-friendly and intuitive platform that makes it easy to turn insights into action and fosters a culture of creativity, experimentation, and continuous improvement. You will be an essential part of this mission, using your technical expertise to demonstrate how our Data Intelligence Platform can help customers solve their complex data challenges. You'll work with a collaborative, customer-focused team that values innovation and creativity, using your skills to create customized solutions to help our customers achieve their goals and guide their businesses forward. Join us in our quest to change how people work with data and make a better world! 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 #CMEG Pay Range Transparency Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected base salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipated utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here . Zone 1 Pay Range $152,300 — $209,450 USD Zone 2 Pay Range $152,300 — $209,450 USD Zone 3 Pay Range $152,300 — $209,450 USD Zone 4 Pay Range $152,300 — $209,450 USD 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.

Requirements

Must-haves

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-haves

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 #CMEG
Our Commitment to Diversity and Inclusion

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningpythonsqlawsazuregcpmlai

Platform: greenhouse
Effort: quick