Senior Solutions Engineer

Databricks

. Independently lead technical discovery and solution design for customer workloads spanning data engineering, analytics, and machine learning .

Posted 11/10/2026full-timeUnited StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in data engineering and solutions architecture, with proficiency in Python and SQL for developing production-quality code. Capable of leading technical customer engagements and delivering impactful presentations on the Databricks Platform.

Highest-signal resume keywords

Data EngineeringSolutions ArchitecturePython ProgrammingSQL ProficiencyDatabricks Certification

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Data EngineeringSolutions ArchitecturePython ProgrammingSQL ProficiencyLive CodingDistributed Data SystemsApache SparkDelta LakeCloud Platform ExperienceTechnical Pre-Sales

Soft Skills

Strong Presentation SkillsTechnical Customer EngagementCommunication SkillsProblem-Solving

Tools & Technologies

Databricks PlatformUnity CatalogLakeflow Spark Declarative PipelinesMLflowAWSAzureGCP

Certifications & Qualifications

Databricks Certification

Industry Keywords

Data/AI CompanyCloud ProviderTechnical Consulting Firm

Tech Stack

Tools & technologies

ApacheAWSAzureCloudGoogle Cloud PlatformHadoopKafkaPythonSparkSQLUnity

About the role

Key responsibilities & impact

Independently lead technical discovery and solution design for customer workloads spanning data engineering, analytics, and machine learning
Build and deliver proofs-of-concept and live demos on the Databricks Platform
Own frontline technical relationships with customer engineers, data teams, and technical leads
Develop account-level technical strategies with the Account Executive to grow platform consumption
Articulate Databricks differentiation through hands-on demonstrations in competitive situations
Contribute reusable technical assets, including notebooks, solution accelerators, and reference architectures
Independently lead customer engagements covering discovery, solution design, and platform demonstrations
Combine coding, architecture, and presenting to drive Databricks adoption

Requirements

What you’ll need

4+ years in data engineering, solutions architecture, technical pre-sales, or a hands-on consulting role
Proficient in Python and SQL; 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 such as Hadoop, Kafka, or Flink
Experience leading technical customer conversations, including discovery, whiteboarding, and architecture reviews
Familiarity with data engineering, data science/ML, or SQL analytics
Strong presentation and demo skills
Ability to 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
Databricks certification or Databricks Platform experience preferred
Experience with Unity Catalog, Lakeflow Spark Declarative Pipelines, or MLflow preferred
Background at a data/AI company, cloud provider, or technical consulting firm preferred

Benefits

Comp & perks

Comprehensive benefits and perks; specific regional details provided via the employer's benefits document