Backline Platform Manager

Job Description

At Databricks, we are passionate about enabling data 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 — and customer-obsessed — we leap at every opportunity to tackle technical challenges, from designing next-gen UI/UX for interfacing with data to scaling our services and infrastructure across millions of virtual machines. And we're only getting started.

About the Team

The Backline Engineering Team serves as the critical bridge between Engineering and Frontline Support. We handle complex technical issues and escalations across the Apache Spark™ ecosystem and the Databricks Platform stack. 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 improvements to the platform.

We emphasize automation and tooling to enhance troubleshooting efficiency, reduce manual efforts, and improve the overall supportability of the platform. By developing smart solutions and streamlining workflows, we drive operational excellence and ensure a seamless experience for both customers and internal teams.

The impact you will have

• Hire and develop top talent to build an outstanding team.


• Mentor engineers, provide clear feedback, and develop future leaders in the team.


• Establish and maintain high standards in troubleshooting, automation, and tooling to improve efficiency.


• Work closely with Engineering to enhance observability, debugging tools, and automation, reducing escalations.


• Collaborate with Frontline Support, Engineering, and Product teams to improve customer escalations and support processes.


• Define a long-term roadmap for Backline, focusing on automation, tool development, bug fixing and proactive issue resolution.


• Take ownership of high-impact customer escalations by leading critical incident response during Databricks runtime outages and major incidents. 


• Participate in weekday and weekend on-call rotations, ensuring fast and effective resolution of urgent issues. Balance real-time escalations with day-to-day planning, and multitasking efficiently to drive operational excellence and provide top-tier support for mission-critical customer environments.

What We Look For:

• 10-12 years of experience in Big Data/Data warehousing, with at least 3+ years in a managerial role.


• Proven ability to manage and mentor a team of Backline Engineers, guiding career development


• Strong technical expertise in atleast one of below domains to troubleshoot complex customer issues.




• Linux/OS and Network troubleshooting


• AWS, Azure or GCP Cloud and related services


• SQL-based database systems


• Hadoop/Spark/Other BigData or Distributed Systems


• Troubleshooting Python and/or Java based applications




• Ability to oversee and drive customer escalations, ensuring seamless coordination between Frontline Support and Backline Engineering.


• Experience in designing and developing best practices, runbooks/playbooks, and enablement programs to improve troubleshooting efficiency.


• Strong automation mindset, identifying tooling and process gaps, and leading efforts to build scripts and automated tools to enhance support operations.


• Skilled in collaborating with Engineering and Product Management teams, contributing to support readiness programs and shaping product supportability improvements.


• Experience in building monitoring and alerting mechanisms, proactively identifying long-running cases and driving early intervention.


• Ability to handle critical technical escalations, providing deep expertise in architecture, best practices, product functionality, performance tuning, and cloud operations.


• Strong interviewing and hiring capabilities, identifying and recruiting top Backline talent with expertise in big data and cloud ecosystems.