2 months ago

Staff Designated Support Engineer

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 1 hour agoStatus: Live

Job Summary

Join Databricks as a Staff Technical Designated Engineer to deliver high-touch, specialized support for our largest customers. You’ll troubleshoot Spark, SQL, Delta, and ML/AI workloads, build rapid POCs, create playbooks, and train customer teams while collaborating with Field, Engineering, Sales, and Product to accelerate production-ready solutions and strengthen customer trust.

Location: Japan

Workplace: Onsite

Employment Type: Full time

Job Function: Design (Product/UX/UI/Visual)

Key Responsibilities

•Collaborate with Field Engineering, Sales, and Product teams to provide rapid technical solutions during customer engagements and presentations.
•Triage and resolve complex product issues and unblock critical technical challenges in Spark, SQL, Delta, and Databricks runtime features.
•Develop and maintain comprehensive playbooks and a knowledge base for Spark, ML, and AI workflows, enabling self-service solutions.
•Build rapid proofs-of-concept, test, deploy, and monitor solutions built by Databricks Engineering to address customer challenges and showcase runtime capabilities.
•Train customer engineering and business teams on best practices in performance tuning, debugging, and effectively leveraging Databricks features.

Key Requirements

•8–12 years of experience designing, building, and troubleshooting distributed computing applications, with 4+ years delivering production-scale Spark/ML/AI solutions using Python, Java, or Scala.
•Hands-on expertise with Data Lakes, SQL-based databases, and Cloud-based Data Warehousing/ETL tools like Snowflake, Redshift, BigQuery, etc
•Deep knowledge of Spark core internals, Delta/Iceberg, JVM optimization, and memory management, with proficiency in AI ecosystems like Machine Learning, Deep Learning, and Generative AI
•Practical experience with AWS, Azure, or GCP, coupled with expertise in building and managing CI/CD pipelines, monitoring, and alerting systems
•3–5 years in customer-facing roles such as Technical Account Manager or Solutions Architect, demonstrating strong communication, relationship-building, and problem-solving skills

Experience:8-12 yearsBig dataData engineeringCloudAIMachine learning

Skills:CommunicationProblem-solvingLeadershipCollaboration

Languages:English

Tech Stack:Apache SparkPythonJavaScalaSnowflakeRedshiftBigQueryDelta LakeIcebergAWSAzureGCPCI/CDSpark UIMosaic AI Model ServiceDatabricksMLflow

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

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Databricks

2 months ago

Staff Designated Support Engineer

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 1 hour agoStatus: Live

Job Summary

Location: Japan

Workplace: Onsite

Employment Type: Full time

Job Function: Design (Product/UX/UI/Visual)

Key Responsibilities

•Collaborate with Field Engineering, Sales, and Product teams to provide rapid technical solutions during customer engagements and presentations.
•Triage and resolve complex product issues and unblock critical technical challenges in Spark, SQL, Delta, and Databricks runtime features.
•Develop and maintain comprehensive playbooks and a knowledge base for Spark, ML, and AI workflows, enabling self-service solutions.
•Build rapid proofs-of-concept, test, deploy, and monitor solutions built by Databricks Engineering to address customer challenges and showcase runtime capabilities.
•Train customer engineering and business teams on best practices in performance tuning, debugging, and effectively leveraging Databricks features.

Key Requirements

•8–12 years of experience designing, building, and troubleshooting distributed computing applications, with 4+ years delivering production-scale Spark/ML/AI solutions using Python, Java, or Scala.
•Hands-on expertise with Data Lakes, SQL-based databases, and Cloud-based Data Warehousing/ETL tools like Snowflake, Redshift, BigQuery, etc
•Deep knowledge of Spark core internals, Delta/Iceberg, JVM optimization, and memory management, with proficiency in AI ecosystems like Machine Learning, Deep Learning, and Generative AI
•Practical experience with AWS, Azure, or GCP, coupled with expertise in building and managing CI/CD pipelines, monitoring, and alerting systems
•3–5 years in customer-facing roles such as Technical Account Manager or Solutions Architect, demonstrating strong communication, relationship-building, and problem-solving skills

Experience:8-12 yearsBig dataData engineeringCloudAIMachine learning

Skills:CommunicationProblem-solvingLeadershipCollaboration

Languages:English

Tech Stack:Apache SparkPythonJavaScalaSnowflakeRedshiftBigQueryDelta LakeIcebergAWSAzureGCPCI/CDSpark UIMosaic AI Model ServiceDatabricksMLflow

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