Job Overview
Location
Remote - Washington
Job Type
Full-time
Category
Software Engineering
Date Posted
May 19, 2026
Full Job Description
đź“‹ Description
- • As a Delivery Solutions Architect (DSA) at Databricks, you will play a critical role in accelerating the adoption and growth of the Databricks Data Intelligence Platform within public sector customers, ensuring technical accountability and driving value realization from deployed workloads.
- • Day to day, you will engage with Solutions Architects to understand use case demand plans, lead post-technical win technical account strategy and execution for strategic accounts, serve as the accountable technical lead for specific use cases across multiple teams, and act as the first point of contact for technical issues related to production/go-live status of agreed-upon workloads.
- • You will collaborate closely with sales, field engineering, Professional Services, User Education, Onboarding/Technical Services, Support, and Product and Engineering teams to coordinate delivery, enablement, adoption, and optimization of Databricks solutions, while creating execution plans covering use case progression, enablement, product adoption, cost optimization, and executive governance.
- • You will report to a DSA Manager within Field Engineering, provide KPI reporting on usage and customer health to technical leadership, and develop strategic roadmaps through discovery workshops and business analysis to maximize customer ROI and platform consumption.
- • This role offers the opportunity to deepen expertise in data and AI solution architecture, technical program management, and executive stakeholder engagement while contributing to mission-critical public sector initiatives using the Databricks Lakehouse platform.
🎯 Requirements
- • U.S. citizenship is required due to federal contract obligations and access to classified information.
- • 7+ years of experience in technical project/program delivery within Data and AI domains, with ability to contribute to technical debates and design choices with customers.
- • Programming experience in Python, SQL, or Scala.
- • Experience in customer-facing pre-sales, technical architecture, customer success, or consulting roles.
- • Understanding of solution architecture for distributed data systems and how to attribute business value to project deliverables.
- • Technical program or project management experience including account, stakeholder, and resource management accountability.
- • Track record of overachievement against quota, goals, or similar objective targets.
- • Bachelor’s degree in Computer Science, Information Systems, Engineering, or equivalent work experience.
- • Ability to travel up to 30% when needed.
🏖️ Benefits
- • Comprehensive benefits and perks designed to meet employee needs, with region-specific details available via internal resources.
- • Commitment to diversity and inclusion, ensuring equitable hiring practices and a workplace where everyone can excel regardless of background.
- • Pay range transparency: $180,000 – $247,500 USD (local pay range for Remote - Washington), with eligibility for annual performance bonus and equity.
- • Access to professional development through collaboration with expert-level technical teams, Product and Engineering, and Shared Services for skill expansion and innovation exposure.
- • Opportunity to work on high-impact public sector projects using the Databricks Data Intelligence Platform, adopted by over 50% of the Fortune 500 and major organizations like Comcast and Condé Nast.
Skills & Technologies
Python
Scala
Apache Spark
Senior
Remote
Degree Required
About Databricks Inc.
Databricks provides a unified data and AI platform built on Apache Spark. Its lakehouse architecture combines data lakes and warehouses to enable collaborative analytics, machine learning, and real-time processing at scale. The company offers managed cloud services, Delta Lake storage, MLflow for ML lifecycle, and collaborative notebooks. Founded in 2013 by the creators of Spark, Databricks serves enterprises seeking to unify data engineering, data science, and business analytics on a single platform.
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