Sr. Manager – Data & AI Support Engineering

Навыки

• AWS
• Azure
• Работа с бэклогом
• Big Data
• Customer Success
• Data Lake
• Распределённые системы

О компании и продукте

• 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 .

Задачи

• 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
• 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
• Participate in major incident management, escalation handling, on-call rotations, and critical production support activities

Требования

• 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
• 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
• 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

Условия

• At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees
• Conduct regular one-on-ones, annual review, and career development discussions with direct reports

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