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Senior Staff Backline Engineer - Data & AIDatabricks · Dallas, Texas; San Francisco, California; Vancouver, Canada
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Databricks

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Senior Staff Backline Engineer - Data & AI

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🗓️ Posted 2026-07-24 Dallas, Texas; San Francisco, California; Vancouver, Canada Hybrid ICT
💰 Salary Not shared 📊 Market 20,833 CAD–33,333 CAD/mo

About the Company

At Databricks, we are passionate about enabling Data & AI teams to solve the world's toughest problems - from making the next mode of transportation a reality to accelerating the development of medical breakthroughs. We do this by building and running the world's best data and AI infrastructure platform so our customers can use deep data insights to improve their business. Founded by engineers, we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for data interaction to scaling our services and infrastructure across millions of virtual machines. The Backline Engineering Team serves as the critical bridge between Frontline Support and Engineering. We handle complex technical issues and escalations across the Data and AI ecosystem. With a strong focus on customer success, we are committed to delivering exceptional customer satisfaction by providing deep technical expertise, proactive issue resolution, and continuous platform improvements. We emphasise automation and tooling to enhance troubleshooting efficiency, reduce manual efforts, and improve the overall supportability of the platform and the health of our products. By developing smart solutions and streamlining workflows, we drive operational excellence and ensure a delightful experience for both customers and internal teams.

Responsibilities

  • ● Conduct deep-dive forensics into Spark core internals and the broader Databricks Data and AI ecosystem to resolve high-priority architectural failures and complex system anomalies.
  • ● Perform advanced code-level analysis and resource profiling to identify and mitigate systemic root causes, ensuring the stability and reliability of high-scale production workloads.
  • ● Optimise architectural performance across the Data and AI stack by refining execution parameters and enforcing best practice strategies to maximise resource efficiency and throughput.
  • ● Analyse global issue trends and patterns to partner directly with Product Engineering, influencing the product roadmap and driving initiatives that enhance long-term supportability.
  • ● Develop reproduction frameworks, automated workflows, and AI-driven diagnostic tools that translate complex backline findings into standardised resolution paths to empower and scale the broader organisation.

Requirements

  • ● 10+ years of relevant experience, including deep expertise in one of the three specialized tracks.
  • ● Proven experience in managing both customers and technical stakeholders.
  • ● Data Engineering Track: Expertise in large-scale big data solutions and ETL pipelines using Spark, Delta Lake, or Hive.
  • ● Data Engineering Track: Strong experience troubleshooting failures, diagnosing performance issues, and identifying root causes.
  • ● Data Engineering Track: Demonstrated problem-solving ability and understanding of data engineering best practices to ensure reliable, efficient workflows.
  • ● Data Engineering Track: Solid hands-on programming skills in Python, SQL, or Scala.