Sr. Manager - Data & AI Support Engineering

Cacheflow; Plano (TX); On-site; USD 140,000 - 180,000; Full time

Benefits offered by this job

Comprehensive benefits

Diversity and inclusion commitment

Job summary

Cacheflow is seeking a Sr. Manager for the Data & AI Support Engineering team in Plano, Texas. You will lead a team of Technical Solutions Engineers to resolve complex customer issues and implement AI-first operational innovations.

Your extensive experience with large-scale Data & AI applications, including Apache Spark and distributed technologies, will be critical in achieving operational excellence and enhancing customer outcomes.

The role involves building AI-enabled workflows and collaborating closely with Engineering teams for support innovation.

Qualifications

• 10+ years of experience with large-scale Data & AI applications.
• Hands-on experience in AI tools for troubleshooting and root-cause analysis.
• Strong analytical and problem-solving skills.

Responsibilities

• Lead and scale the AI-first Data & AI Support Engineering organization.
• Drive AI-first support transformation initiatives.
• Build and scale reusable AI-enabled workflows and automations.

Skills

Python

Java

Scala

Apache Spark

AI-enabled support workflows

Distributed systems troubleshooting

Data processing systems

Cloud platforms (AWS, Azure, GCP)

Job description

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 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.

Benefits

At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all our employees. For specific details on the benefits offered in your region, please refer to the internal benefits portal.

Our Commitment to Diversity and Inclusion

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.

Compliance

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.