Senior Partner Solutions Architect – Customer Lake, Lakewatch

Databricks

. Serve as an expert-level technical leader accelerating platform adoption and scaling growth across strategic partner ecosystems, including SIs, GSIs, ISVs, and cloud providers .

Posted 11/3/2026full-timeRemote • California • United StatesSenior💰 $219,100 - $301,300 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expert-level technical leadership in solutions architecture and partner technical management, with a strong focus on driving platform adoption and growth through strategic partnerships. Proficient in developing enablement kits and reference architectures while guiding partner engineering teams in deploying advanced data solutions.

Highest-signal resume keywords

Solutions ArchitectureExpert-Level Coding Proficiency in PythonDeep Expertise in Enterprise Data ArchitectureDatabricks Platform KnowledgeExperience with Cloud Providers (AWS, Azure, GCP)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

PythonSQLSparkData GovernanceReal-Time ArchitecturesData ObservabilityAutomated Data QualityLakewatchCustomer Lake Design PatternsDistributed Systems

Soft Skills

Strategic ThinkingInfluencing StakeholdersCollaboration

Tools & Technologies

DatabricksAWSAzureGCPLakewatch

Certifications & Qualifications

Databricks Certifications

Industry Keywords

Cloud ProvidersSystem IntegratorsStrategic Technology PartnersEnterprise EvaluationsData/AI Companies

Tech Stack

Tools & technologies

AWSAzureCloudDistributed SystemsGoogle Cloud PlatformPySparkPythonSnowflakeSparkSQL

About the role

Key responsibilities & impact

Serve as an expert-level technical leader accelerating platform adoption and scaling growth across strategic partner ecosystems, including SIs, GSIs, ISVs, and cloud providers
Train and enable partner technical teams to build repeatable, high-value practices around Customer Lake and Lakewatch
Co-architect complex partner solutions that accelerate customer adoption, deployment velocity, and platform usage across Customer Lake environments
Guide partner engineering teams in deploying Lakewatch for automated data quality monitoring and health telemetry
Advise partner CTOs, Chief Architects, and Practice Leads, aligning technology roadmaps with Customer Lake and Lakewatch innovations
Develop enablement kits, reference architectures, and deployment blueprints for partner integration and rollout
Collaborate with Field Engineering, Product, and Partner Management teams on unified partner go-to-market initiatives
Complete the interview process, including design and architecture interview, live coding assessment, build/demo/pitch presentation, and reference check

Requirements

What you’ll need

8+ years in solutions architecture, partner technical management, principal engineering, or senior customer-/partner-facing technical pre-sales roles
Proven experience working with system integrators, cloud providers (AWS, Azure, GCP), or strategic technology partners (ISVs)
Expert-level coding proficiency in Python and SQL; ideally Spark/PySpark
Must complete a live coding assessment and platform build during the interview
Deep expertise in enterprise data architecture, including distributed systems, real-time/streaming, Customer Lake design patterns, data governance frameworks, and cloud-native platforms
Deep knowledge of data observability, automated data quality, and platform telemetry using Lakewatch or equivalent monitoring tools
Expert-level Databricks Platform knowledge or equivalent depth in competing platforms with demonstrated rapid learning ability
Declared technical specialization with recognized depth, such as real-time architectures, ML/AI platforms, data governance, large-scale migrations, or industry-specific solutions
Proven track record driving consumption growth and platform adoption in large accounts
Ability to influence VPs, Practice Directors, 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
Databricks certifications are nice to have
Prior experience at Databricks, Snowflake, AWS, Google, Microsoft, or a top-tier data/AI company is nice to have
Published thought leadership is nice to have
Industry vertical expertise with executive-level domain credibility is nice to have
If access to export-controlled technology or source code is required, employment may depend on U.S. government licensing discretion

Benefits

Comp & perks

Annual performance bonus eligibility
Equity eligibility
Comprehensive benefits and perks (specific regional details provided via Databricks benefits documentation)