Databricks

1 month ago

Sr. Manager – Data & AI Support Engineering

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 8 hours agoStatus: Live

Job Summary

Lead a global Data & AI Support Engineering team to deliver AI-enabled, high-velocity technical support for Spark, AI/ML, Streaming, and Lakehouse workloads. Drive AI-first workflows, governance, and cross-functional collaboration with Engineering and Product to improve resolution times, platform reliability, and customer outcomes across enterprise-scale deployments.

Location: Dallas

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Sr. Manager level

Key Responsibilities

•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.
•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.

Key Requirements

•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:DataAiSparkMlStreamingLakehouseDistributed systemsObservability

Skills:CommunicationLeadershipProblem-solving

Languages:English

Tech Stack:PythonJavaScalaSparkSpark SQLStructured StreamingDelta LakeLakehouseDLTAWSAzureGCPJira

Company Brief

Databricks

Provides a unified data analytics platform powered by Apache Spark to simplify building, deploying, and scaling data engineering, data science, and machine learning workloads for enterprises.

Industry: Data Infrastructure

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series E+

Headquarters: San Francisco, United States

Founded: 2013

Website LinkedIn

Loading job details...

Preparing the role view and application actions.

Databricks

1 month ago

Sr. Manager – Data & AI Support Engineering

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 8 hours agoStatus: Live

Job Summary

Location: Dallas

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Sr. Manager level

Key Responsibilities

•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.
•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.

Key Requirements

•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:DataAiSparkMlStreamingLakehouseDistributed systemsObservability

Skills:CommunicationLeadershipProblem-solving

Languages:English

Tech Stack:PythonJavaScalaSparkSpark SQLStructured StreamingDelta LakeLakehouseDLTAWSAzureGCPJira

Company Brief

Databricks

Provides a unified data analytics platform powered by Apache Spark to simplify building, deploying, and scaling data engineering, data science, and machine learning workloads for enterprises.

Industry: Data Infrastructure

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series E+

Headquarters: San Francisco, United States

Founded: 2013

Website LinkedIn