Databricks
Sr.Manager–Data&AISupportEngineering
Neural analysis suggests this role is
optimal for Manager candidates.
“Sr. Manager – Data & AI Support Engineering at Databricks. Skills: AI-first support, Technical Solutions Engineering. Lead and manage Technical Solutions Engineers. Drive deep technical resolutions for customer issues”
What You'll Achieve.
Improve resolution speed; Improve support quality; Drive exceptional customer outcomes; Improve platform reliability; Improve case quality; Improve operational efficiency; Improve customer experience; Drive faster resolutions
Industry & Context.
Analytical skills; Debugging skills; Problem-solving skills; Distributed systems troubleshooting skills; Troubleshooting; Performance tuning; Root-cause analysis
On-call rotations
What They're Looking For.
Must Have
10+ years experience designing, building, troubleshooting, supporting Data & AI applications, 10+ years experience using Python, Java, Scala, Spark, Work experience of AI-enabled support workflows, Work experience of agentic AI systems, Work experience of Claude Skills workflows, Work experience of RAG architectures, Work experience of vector databases, Work experience of operational automation frameworks, Proven development/delivery experience at production scale, Experience using AI tools for troubleshooting, Experience using AI tools for root-cause analysis, Experience using AI tools for observability analysis, Experience using AI tools for support workflow acceleration, Hands-on expertise in Apache Spark, Hands-on expertise in Spark SQL, Hands-on expertise in Structured Streaming, Hands-on expertise in Delta Lake, Hands-on expertise in distributed data processing systems, Experience leading production-scale workloads, Troubleshooting and performance tuning experience for Spark, Troubleshooting and performance tuning experience for JVM-based distributed systems, Hands-on experience with AWS, Hands-on experience with Azure, Hands-on experience with GCP, Proven experience managing globally distributed technical teams, Proven experience handling high-severity customer escalations
Nice to Have
Databricks tech stacks experience a plus, Model serving experience a plus, Lakehouse experience a plus, Delta experience a plus, DLT experience a plus, Lakeflow experience a plus, Lakebase platforms experience a plus
What You'll Do.
Lead and manage Technical Solutions Engineers
Drive deep technical resolutions for customer issues
Help customers realize business value
Scale AI-first Data & AI Support Engineering organization
Combine technical expertise and operational excellence
Improve platform reliability
Drive exceptional customer outcomes
Build AI-enabled support workflows
Build reusable automations
Improve resolution speed
Improve support quality
Use Agentic AI systems for troubleshooting
Use logs for troubleshooting
Use telemetry for troubleshooting
Use observability platforms for troubleshooting
Use internal systems for troubleshooting
Accelerate troubleshooting
Accelerate root-cause analysis
Create reusable runbooks
Create reusable prompts
Create reusable agentic workflows
Scale operational efficiency
Ensure customer data safety
Ensure validation practices
Ensure human-in-the-loop controls
Partner with Engineering teams
Partner with Product teams
Drive AI-first support innovation
Drive operational excellence
Drive AI-first support transformation initiatives
Improve operational efficiency
Improve customer experience
Operationalize AI-assisted diagnostics
Operationalize observability insights
Operationalize intelligent escalation management
Build reusable AI-enabled workflows
Build reusable automations
Build reusable runbooks
Build reusable operational intelligence frameworks
Lead Technical Solutions Engineers
Lead support operations personnel
Own and improve operational KPIs
Improve customer satisfaction
Improve escalation management
Improve backlog health
Improve resolution efficiency
Improve support quality
Act as senior escalation point
Drive operational excellence
Drive process optimization
Lead technical assessments
Lead career development
Conduct regular one-on-ones
Conduct annual reviews
Conduct career development discussions
Support complex issues
Guide customers on Spark runtime optimization
Guide customers on distributed systems performance
Guide customers on best practices
Own Engineering JIRA escalations
Drive faster resolutions for product issues
Maintain internal operational documentation
Maintain customer-facing knowledge base assets
Coordinate with Engineering
Coordinate with Backline Support engineering
Coordinate with customer experience intelligence teams
Identify product defects
Reproduce product defects
Report product defects
Act as customer advocate
Collaborate with cloud partners
Support mutual customer success
Participate in major incident management
Participate in escalation handling
Participate in on-call rotations
Participate in critical production support activities
How You'll Work.
Team & Collaboration
Partner with Engineering teams; Partner with Product teams; Coordinate with Engineering; Collaborate with cloud partners
Communication Scope
Written communication; Verbal communication; Customer-facing leadership
Process & Methodology
JIRA escalations
Full Job Description
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 manage Technical Solutions Engineers, Team Leads, and support operations personnel across AMER support functions based out of the
Applying for this Sr. Manager – Data & AI Support Engineering role?
Most applicants get filtered before a human reads their resume. See if yours makes the cut.
ANONYMOUS · UNFILTERED
What do employees actually say about Databricks?
Real rants from real employees. Read before you apply.