Sr. Partner Solutions Architect - Customer Lake & Lakewatch
Databricks8 days ago
Base Salary
$219k - $301k/yr
Responsibilities
- Train and enable partner technical teams to build repeatable practices around Customer Lake and Lakewatch.
- Co-architect complex partner solutions that accelerate customer adoption, deployment velocity, and platform consumption.
- Guide partner engineering teams in deploying Lakewatch for automated data quality monitoring and system telemetry.
- Advise partner CTOs, chief architects, and practice leads on technology roadmaps and platform innovations.
- Develop enablement kits, reference architectures, and deployment blueprints for partner integration and rollout.
- Coordinate Field Engineering, Product, and Partner Management teams on partner go-to-market initiatives.
- Drive competitive displacements, complex enterprise evaluations, and platform adoption in large accounts.
Requirements
- 8+ years of experience in solutions architecture, partner technical management, principal engineering, or senior customer- or partner-facing technical pre-sales roles.
- Experience working with system integrators, global system integrators, cloud providers, or strategic technology partners.
- Expert-level proficiency in Python and SQL, with Spark or PySpark preferred; candidates complete a live coding assessment and platform build.
- Deep expertise in distributed systems, real-time or streaming architectures, Customer Lake design patterns, data governance, cloud-native platforms, data observability, automated data quality, and platform telemetry.
- Expert-level Databricks Platform knowledge or equivalent expertise in competing platforms.
- Recognized technical specialization in areas such as real-time architectures, ML/AI platforms, data governance, large-scale migrations, or industry-specific solutions.
- Proven record of driving consumption growth, platform adoption, competitive displacements, and complex enterprise evaluations.
- Executive presence and ability to influence VPs, practice directors, and C-level stakeholders on data and AI strategy.
- Bachelor's or Master's degree in Computer Science, Engineering, or a quantitative discipline, or equivalent experience.
- Preferred qualifications include Databricks certifications, experience at Databricks, Snowflake, AWS, Google, Microsoft, or a top-tier data/AI company, published thought leadership, and industry vertical expertise.
Benefits
- The compensation package may include annual performance bonus, equity, and regional benefits; specific benefits vary by location.
Tech Stack
Categories
Solutions Engineering
About Databricks
Databricks builds a cloud-based data and AI platform centered on the lakehouse architecture, combining data engineering, analytics, and machine learning with Apache Spark, Delta Lake, and MLflow. It sells subscriptions and cloud services to enterprises that need to unify data pipelines and develop large-scale AI and analytics. Founded in 2013 by the creators of Apache Spark and headquartered in San Francisco, the company is privately held and serves organizations across many industries.