Sr. Manager – Data & AI Support Engineering

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.

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 Dallas location.

• Own and improve operational KPIs including customer satisfaction,

escalation management, backlog health, resolution efficiency, and support quality.

• Act as a senior escalation point for

customers and internal teams while driving operational excellence and process optimization.

• Lead hiring, onboarding,

mentoring, technical assessments, training, and career development for support engineers and technical leads.

• Conduct

regular one-on-ones, annual review, and career development discussions with direct reports.

• Be a hands-on technical

leader supporting complex issues related to Spark Core, Spark SQL, Structured Streaming, Delta Lake, Lakehouse architecture, and

Databricks Runtime technologies.

• Guide customers on Spark runtime optimization, distributed systems performance, and best

practices for scalable Data & AI workloads.

• Own Engineering JIRA escalations and proactively drive faster resolutions

for customer-reported product issues.

• Maintain internal operational documentation, runbooks, and customer-facing

knowledge base assets.

• Coordinate closely with Engineering and Backline Support engineering, customer experience

intelligence teams to identify, reproduce, and report product defects effectively.

• Act as a strong customer advocate and

collaborate with cloud partners to support mutual customer success.

• Participate in major incident management, escalation

handling, on-call rotations, and critical production support activities.

What we are looking for:​

• 10+

years of experience designing, building, troubleshooting, and supporting large-scale Data & AI applications using Python,

Java, Scala, Spark, or related distributed technologies.

• Strong work experience of AI-enabled support workflows, agentic

AI systems, Claude Skills workflows, RAG architectures, vector databases and any other operational automation frameworks.

• Proven development/delivery experience at a production scale in Databricks tech stacks like Model serving, Lakehouse, Delta,

DLT, Lakeflow, Lakebase platforms is a strong plus.

• Experience using AI tools for troubleshooting, root-cause analysis,

observability analysis, and support workflow acceleration.

• Strong hands-on expertise in Apache Spark, Spark SQL,

Structured Streaming, Delta Lake, and distributed data processing systems.

• Experience leading production-scale workloads

across Big Data, Hadoop, AI/ML, Kafka, Streaming, Data Science, or Analytics platforms.

• Strong troubleshooting and

performance tuning experience for Spark and JVM-based distributed systems, including memory management, garbage collection, heap

analysis, and thread dump analysis.

• Hands-on experience with AWS, Azure, or GCP cloud platforms.
• Proven

experience managing globally distributed technical teams and handling high-severity customer escalations.

• Strong

analytical, debugging, problem-solving, and distributed systems troubleshooting skills.

• Excellent written and verbal

communication skills with strong customer-facing leadership abilities.

• Strong organizational, multitasking, stakeholder

management, and operational leadership capabilities.

About

Databricks​

Databricks is the Data and AI company. More than 20,000

organizations worldwide — including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 —

rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San

Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks,

Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.

​At Databricks,

we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the

benefits offered in your region click here.

At Databricks, we are committed to fostering a diverse and

inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal

employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color,

disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental

ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected

characteristics.

If access to export-controlled

technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a

U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis

alone.​