Sr. Manager – Data & AI Support Engineering
Databricks - Plano, Texas
Posted Jun 4, 2026
Benefits
- Parental leave
- Not verified
- Non-birth-parent leave
- Not verified not verified - source URL not recorded; timestamp not recorded
- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Verification
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- Salary
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- 401(k) match
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Market context
- U.S. role benchmark (BLS OEWS)
- $111,944 U.S. median for this role
- Projected growth (BLS Employment Projections)
- +13.7% - Much faster than average
Matched to SOC 15-1252 - Data and ML aggregate by role bucket.
Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.
Role
Schedule
- Shift type
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- Weekend work
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Application
- Cover letter
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- Assessment
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- Deadline
- Not stated
Where they hire
State eligibility is not yet verified.
About this role
Sr. Manager – Data & AI Support Engineering Plano, Texas P-1388 As a Sr. Manager of the Data & AI Support Engineering team, you will lead and manage a team of Technical Solutions Engineers responsible for driving deep technical resolutions for complex customer issues across Spark, AI/ML, Streaming, and Lakehouse platforms. You will help customers realize business value from Databricks Ecosystem products through strong technical leadership, AI-first operational innovation and customer-centric execution. Mission Lead and scale a world-class AI-first Data & AI Support Engineering organization that combines deep technical expertise, operational excellence, intelligent automation and customer-centric support to accelerate issue resolution, improve platform reliability and drive exceptional customer outcomes across enterprise-scale Data and AI workloads. - Build AI-enabled support workflows and reusable automations to improve resolution speed and support quality. - Use Agentic AI systems, logs, telemetry, observability platforms and internal systems to accelerate troubleshooting and root-cause analysis safely. - Create reusable runbooks, prompts, and agentic workflows that scale operational efficiency across teams. - Ensure strong AI governance, customer data safety, validation practices, auditability, and human-in-the-loop controls. - Partner with Engineering and Product teams to drive AI-first support innovation and operational excellence. Outcomes - Drive AI-first support transformation initiatives that improve resolution speed, case quality, operational efficiency and customer experience. - Partner with Engineering and Product teams to operationalize AI-assisted diagnostics, observability insights, and intelligent escalation management for enterprise customers. - Build and scale reusable AI-enabled workflows, automations, runbooks, and operational intelligence frameworks across the support organization. - Lead and
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