⏳ Last Date to Apply: Not Mentioned
Databricks Delivery Solutions Architect Recruitment 2026: Apply Online
Delivery Solutions Architect – High-Tech & Manufacturing
Job Overview
About the Delivery Solutions Architect Role
At Databricks, our mission is to empower customers to solve the world’s toughest data problems by utilizing the Databricks Data Intelligence Platform. As a Delivery Solutions Architect (DSA) for High-Tech & Manufacturing, you will play a pivotal role in this journey. You will collaborate closely with our sales and field engineering teams to accelerate the adoption and growth of the Databricks platform within your assigned customer accounts. By providing technical accountability and strategic guidance, you will help our most complex customers maximize the return on their investment and unlock the full value of their data workloads.
A Hybrid Technical and Commercial Opportunity
This position is a unique hybrid of technical leadership and commercial strategy. On the commercial side, you will drive growth and platform consumption by building strong executive relationships, leading customer stakeholders, and orchestrating specialized internal teams. On the technical side, you will serve as the post-sale technical lead across the entire Databricks product suite. This requires deep technical credibility and the ability to communicate complex architectural concepts to both developers and C-level executives. You will be responsible for translating business objectives into robust technical execution plans.
Key Areas of Impact and Responsibility
Your day-to-day activities will focus on driving customer success and platform adoption through several key workstreams:
- Technical Strategy & Execution: Lead the post-technical win strategy for strategic accounts, ensuring a smooth transition from initial win to active production.
- Workload Onboarding: Drive the enablement, onboarding, and healthy consumption of Databricks workloads, creating certainty out of complex technical environments.
- Technical Escalation Management: Act as the primary point of contact for critical technical issues, coordinating with Support and Engineering to resolve roadblocks swiftly.
- Product Adoption & Optimization: Promote the adoption of the Databricks Lakehouse vision while helping customers manage cloud costs, tuning, and optimization.
- Stakeholder Governance: Establish operational and executive governance frameworks, providing regular KPI updates on customer health and usage metrics.
Why Join Databricks?
Databricks is trusted by more than 10,000 organizations globally, including over 50% of the Fortune 500. By joining our team, you will work alongside the original creators of Apache Spark, Delta Lake, and MLflow. We offer a highly collaborative environment, competitive compensation packages (including equity and performance bonuses), and comprehensive benefits designed to support your personal and professional well-being. We are committed to diversity, equity, and inclusion, ensuring that every employee has the resources and support needed to excel.
The High-Tech and Manufacturing sectors present unique data challenges, from supply chain optimization to real-time IoT analytics. As a DSA, you will help customers navigate these challenges by designing scalable architectures that leverage real-time streaming, machine learning, and generative AI. Your expertise will directly influence how some of the world’s largest companies innovate and bring products to market. If you are passionate about data engineering, cloud architecture, and driving tangible business outcomes, this role offers an unparalleled platform to elevate your career.
Key Job Details
| Company Name | Databricks |
| Job Role | Delivery Solutions Architect – High-Tech & Manufacturing |
| Experience | 5+ years of experience in technical project/program delivery within the Data and AI domain. |
| Salary Range | Competitive (Based on location and experience as per Databricks Pay Zone Mapping) |
| Job Type | Full-Time |
| Work Mode | Hybrid |
| Openings | Not Mentioned |
| Job Location | San Francisco, CA (Hybrid) |
Key Responsibilities
- Collaborate with sales and field engineering teams to accelerate adoption and growth of the Databricks platform.
- Act as the post-sale technical lead across all Databricks products for strategic accounts.
- Lead the post-technical win technical account strategy and execution plan.
- Serve as the primary contact for technical issues or questions related to production/go-live status.
- Coordinate with Professional Services resources on delivery proposals.
- Navigate Databricks Product and Engineering teams for new product innovations and upgrades.
- Develop and execute plans covering main use cases, enablement, product adoption, and organic needs.
- Provide internal and external KPI reporting on usage status and customer health.
Requirements & Qualifications
- 5+ years of experience in technical project/program delivery in Data and AI.
- Ability to contribute to technical debate and design choices with customers.
- Experience in customer-facing pre-sales, technical architecture, customer success, or consulting roles.
- Ability to attribute business value and outcomes to specific project deliverables.
- Track record of overachievement against quota, goals, or objective targets.
- Willingness and ability to travel up to 30% when needed.
Required Skills
- Programming experience in Python, SQL, or Scala
- Technical architecture and customer success expertise
- Understanding of distributed data systems solution architecture
- Technical program and project management
- Stakeholder and resource management
- Complex escalation resolution
- Strategic roadmap creation and business analysis
About Databricks
Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow.
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