Senior Solutions Engineer – Digital Native Business

Databricks

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

Posted 9/18/2026full-timeRemote • California • United StatesSenior💰 $152,300 - $209,450 per yearWebsite

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 a strong focus on building and delivering data solutions on cloud platforms. Proficient in Python and SQL, capable of leading technical customer engagements and articulating complex concepts through effective presentations and demonstrations.

Highest-signal resume keywords

Data EngineeringSolutions ArchitecturePython ProgrammingSQL ProficiencyApache Spark

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data EngineeringSolutions ArchitecturePython ProgrammingSQL ProficiencyApache SparkDelta LakeCloud Platform ExperienceTechnical Pre-SalesLive CodingData Solutions Design

Soft Skills

Presentation SkillsCustomer EngagementTechnical CommunicationProblem SolvingCollaboration

Tools & Technologies

Databricks PlatformUnity CatalogLakeflow Spark Declarative PipelinesMLflowDistributed Data Systems

Certifications & Qualifications

Databricks Certification

Industry Keywords

Data EngineeringData ScienceMachine LearningTechnical ConsultingCloud Provider

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 technical engagements, owning discovery, solution design, and platform demonstrations

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 (Hadoop, Kafka, 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
Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline, or equivalent experience
Databricks certification or Databricks Platform experience is nice to have
Experience with Unity Catalog, Lakeflow Spark Declarative Pipelines, or MLflow is nice to have
Background at a data/AI company, cloud provider, or technical consulting firm is nice to have

Benefits

Comp & perks

Eligibility for annual performance bonus
Equity
Comprehensive benefits and perks (specific regional details provided via employer benefits documentation)