Databricks

1 year ago

Senior Staff Backline Engineer - Data & AI

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

A senior backline engineer focused on diagnosing and resolving complex data and AI system issues. You’ll perform deep-dive troubleshooting, root-cause analysis, and architectural optimization across the Databricks Data & AI stack, working with product engineering and customer stakeholders to improve platform reliability, scalability, and supportability. You’ll build tooling and frameworks to automate diagnostics and influence the product roadmap.

Location: Dallas, San Francisco, Vancouver

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Deep Dive Troubleshooting: conduct forensics into Spark core internals and the Databricks Data & AI ecosystem to resolve high-priority issues
•Root Cause Analysis: perform code-level analysis and profiling to identify systemic root causes and ensure stability of high-scale workloads
•Architectural Optimization: refine execution parameters to maximize resource efficiency and throughput
•Product Improvements: analyze trends and partner with Product Engineering to influence the roadmap and improve long-term supportability
•Scalability & Tooling: develop reproduction frameworks and automated workflows to translate backline findings into standardized resolution paths

Pay and Benefits

Salary: USD 170.4 - 255.6 hourly

Key Requirements

•10+ years of relevant experience in one of three tracks (Data Engineering, Product Supportability, or AI) with experience managing both customers and technical stakeholders
•Data Engineering Track: expertise in Spark, Delta Lake, Hive; strong Python, SQL, or Scala programming
•Product Supportability Track: strong understanding of distributed system internals; code-level root-cause analysis in Java, Scala, or Python
•AI Track: experience with large-scale machine learning and distributed AI systems, including governance and deployment
•customer-obsessed mindset with ability to influence product roadmap and drive improvements

Experience:10+ yearsData engineeringAIBig dataDistributed systems

Skills:Customer focusProblem solvingCommunicationStakeholder managementTeam collaboration

Languages:English

Tech Stack:SparkDelta LakeHivePythonSQLScalaJava

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

1 year ago

Senior Staff Backline Engineer - Data & AI

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 2 hours agoStatus: Live

Job Summary

Location: Dallas, San Francisco, Vancouver

Workplace: Onsite

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Deep Dive Troubleshooting: conduct forensics into Spark core internals and the Databricks Data & AI ecosystem to resolve high-priority issues
•Root Cause Analysis: perform code-level analysis and profiling to identify systemic root causes and ensure stability of high-scale workloads
•Architectural Optimization: refine execution parameters to maximize resource efficiency and throughput
•Product Improvements: analyze trends and partner with Product Engineering to influence the roadmap and improve long-term supportability
•Scalability & Tooling: develop reproduction frameworks and automated workflows to translate backline findings into standardized resolution paths

Pay and Benefits

Salary: USD 170.4 - 255.6 hourly

Key Requirements

•10+ years of relevant experience in one of three tracks (Data Engineering, Product Supportability, or AI) with experience managing both customers and technical stakeholders
•Data Engineering Track: expertise in Spark, Delta Lake, Hive; strong Python, SQL, or Scala programming
•Product Supportability Track: strong understanding of distributed system internals; code-level root-cause analysis in Java, Scala, or Python
•AI Track: experience with large-scale machine learning and distributed AI systems, including governance and deployment
•customer-obsessed mindset with ability to influence product roadmap and drive improvements

Experience:10+ yearsData engineeringAIBig dataDistributed systems

Skills:Customer focusProblem solvingCommunicationStakeholder managementTeam collaboration

Languages:English

Tech Stack:SparkDelta LakeHivePythonSQLScalaJava

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