Most Loved Workplace® Certified Job

Senior Staff Backline Engineer - Data & AI

Most Loved Workplace® Certified Job

92% of candidates apply because they are a Most Loved Workplace®

Dallas, Texas; San Francisco, California; Vancouver, Canada

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About the Role

At Databricks, a Most Loved Workplace® certified employer in the Technology space, Democratizing data and AI for every organization worldwide.

<p>At Databricks, we are passionate about enabling Data &amp; 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. And we're only getting started.</p>

<h3><strong>About the Team: </strong></h3>

<p>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.</p>

<h3><strong>What your impact will be:</strong></h3>

<ul>

<li><strong>Deep Dive Troubleshooting</strong>: 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.</li>

<li><strong>Root Cause Analysis</strong>: 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.</li>

<li><strong>Architectural Optimization</strong>: Optimise architectural performance across the Data and AI stack by refining execution parameters and enforcing best practice strategies to maximise resource efficiency and throughput.</li>

<li><strong>Product Improvements</strong>: Analyse global issue trends and patterns to partner directly with Product Engineering, influencing the product roadmap and driving initiatives that enhance long-term supportability.<br>Scalability &amp; Tooling: 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.</li>

</ul>

<p>We are looking for customer-obsessed candidates with 10+ years of relevant experience, including deep expertise in one of the following three specialized tracks, along with proven experience in managing both customers and technical stakeholders. <em><strong>Since each track calls for a different set of technical capabilities, we’re looking for excellence in one area rather than proficiency in al</strong></em>l:&nbsp;</p>

<ul>

<li><strong>Data Engineering Track</strong>: Expertise in large-scale big data solutions and ETL pipelines using Spark, Delta Lake, or Hive. Strong experience troubleshooting failures, diagnosing performance issues, and identifying root causes. Demonstrated problem-solving ability and understanding of data engineering best practices to ensure reliable, efficient workflows. Solid hands-on programming skills in Python, SQL, or Scala.</li>

<li><strong>Product Supportability Track</strong>: Deep understanding of distributed system internals. Ability to perform code-level root-cause analysis and profiling (using metrics and heap/thread dumps) in Java, Scala, or Python. Proven record of contributing to bug fixes and mentoring other engineers.</li>

<li><strong>AI Track</strong>: Experience with large-scale machine learning and generative AI systems, including LLM-based applications and agent-driven workflows. Strong grasp of model training, evaluation, and deployment in distributed environments. Experience managing the ML lifecycle, including governance and operationalisation. Skilled in diagnosing and optimising distributed ML workloads for performance and scalability.</li>

</ul>

<p><strong>Pay Range Transparency</strong></p>

<p><span style="font-weight: 400; font-size: 14px;">Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles.&nbsp; Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page <a href="https://www.Databricks.com/sites/default/files/2024-08/us-pay-zone-mapping.pdf">here</a>.<br></span></p>

<p>&nbsp;</p></div><div class="title">Local Pay Range</div><div class="pay-range"><span>$170.40</span><span class="divider">&mdash;</span><span>$255.60 USD</span></div></div></div><div class="content-conclusion"><p><strong>About Databricks</strong></p>

<p><span style="font-family: arial, sans-serif;">Databricks is the data and AI company. More than 10,000 organizations worldwide — including Comcast, Condé Nast, Grammarly, and over 50% of the Fortune 500 — rely on the Databricks Data Intelligence Platform to unify and democratize data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe and was founded by the original creators of Lakehouse, Apache Spark™, Delta Lake and MLflow. To learn more, follow Databricks on&nbsp;<span style="color: rgb(255, 54, 33);"><a style="color: rgb(255, 54, 33);" href="https://twitter.com/Databricks" target="_blank" data-saferedirecturl="https://www.google.com/url?q=https://twitter.com/Databricks&amp;source=gmail&amp;ust=1700237575733000&amp;usg=AOvVaw03FL8fJvOD97ytN02f5G2C">Twitter</a>,&nbsp;<a style="color: rgb(255, 54, 33);" href="https://www.linkedin.com/company/Databricks" target="_blank" data-saferedirecturl="https://www.google.com/url?q=https://www.linkedin.com/company/Databricks&amp;source=gmail&amp;ust=1700237575733000&amp;usg=AOvVaw15dLk3q8VxTfHEgCUg7NSt">LinkedIn</a>&nbsp;<span style="color: rgb(0, 0, 0);">and</span>&nbsp;<a style="color: rgb(255, 54, 33);" href="https://www.facebook.com/databricksinc" target="_blank" data-saferedirecturl="https://www.google.com/url?q=https://www.facebook.com/databricksinc&amp;source=gmail&amp;ust=1700237575733000&amp;usg=AOvVaw39EcncitnlqV72EG2-RqXJ">Facebook</a></span>.<br><br><strong>Benefits<br><br></strong></span>At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click <a href="https://docs.google.com/document/d/154un3e8Xav4BceOSlcYFZRGEuQI54xMxVydRwQn54eQ/edit?usp=sharing">here</a>.<br><br></p>

<p><strong>Our Commitment to Diversity and Inclusion</strong></p>

<p>At Databricks, we are committed to fostering a diverse and inclusive culture where everyone can excel. We take great care to ensure that our hiring practices are inclusive and meet equal employment opportunity standards. Individuals looking for employment at Databricks are considered without regard to age, color, disability, ethnicity, family or marital status, gender identity or expression, language, national origin, physical and mental ability, political affiliation, race, religion, sexual orientation, socio-economic status, veteran status, and other protected characteristics.</p>

<p><strong>Compliance</strong></p>

<p><strong><span style="font-weight: 400;">If access to export-controlled technology or source code is required for performance of job duties, it is within Employer's discretion whether to apply for a U.S. government license for such positions, and Employer may decline to proceed with an applicant on this basis alone.</span></strong></p></div>

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Why This Is a Most Loved Workplace® Certified Job

Systemic Collaboration

As Databricks continues our rapid growth, we strive to maintain a culture as open and transparent as it was in Databricks’s early days. Making sure employees have regular access to our CEO and co-founders to hear directly about our vision and priorities helps our employees forge a connection between Databricks priorities and their daily work.

Positive Vision for the Future

Databricks’ culture principles are derived from an internal study of the behaviors that have led to high impact work at Databricks. These values have a direct impact on company culture and play a large part in connecting teams across the organization. We believe in being customer-obsessed, truth-seeking, operating from first principles, having a bias for action, and putting Databricks first. Our co-founders are fully involved in day-to-day operations, including business and technical reviews, working alongside our team members to ensure that we are always aligned with our values.

Alignment of Values

Databricks’ CEO and Co-founder, Ali Ghodsi leads by example with a focus on truth-seeking and first principles thinking, two of Databricks’ core values that stay true to Databricks’s origins in academia. He champions the importance of data and reason to question biases and inform decisions. Ali remains hands-on with research and development and hosts company-wide weekly all hands, with a CEO “ask me anytime” session at the beginning of every agenda. His transparency and accessibility are core to the open and collaborative culture of Databricks.

Respect

At Databricks, we cultivate an environment where all employees can bring their unique selves and are empowered to do the best work of their careers. To ensure all voices are heard and ideas are valued, we conduct annual culture and pulse surveys and host all-hands Q&As to collect feedback from all employees. We then report back to Databricks on the specific changes implemented from the feedback collected to ensure employees feel heard and that their feedback is valued. In addition, we invest in our seven Employee Resource Groups (ERGs) that offer support and employee engagement events for individuals from underrepresented backgrounds and allies.

Killer Outcomes

Databricks prioritizes offering an exceptional employee experience by investing in tools, workspaces, and community-building. Our collaboration-first, hybrid model offers flexibility with in-person touchpoints like our annual employee kickoff, weekly CEO all-hands with happy hours, and monthly team building budgets. We are especially focused on maintaining a culture of transparency, honesty, and trust, with leaders actively engaging across channels like Slack and all hands while also championing inclusion efforts through ERG sponsorship. These initiatives help our team feel connected, valued, and empowered to do their best work.

What It's Like to Work Here

zap Bias for Action

lightbulb First Principles Innovation

users Collaborative Excellence

target Truth-Seeking Rigor

compass Generational Mission Focus

Certified for: Global Top 100 Most Loved Workplaces®, Certified Most Loved Workplaces® 2025, Top 100 Most Loved Workplaces® 2025

Frequently Asked Questions About Working at Databricks

Common questions candidates ask about this role and Databricks's workplace

With the Data Intelligence Platform, Databricks democratizes insights to everyone in an organization. Built on an open lakehouse architecture, the Data Intelligence Platform provides a unified foundation for all data and governance, combined with AI models tuned to an organization’s unique characteristics. Now, anyone in an organization can benefit from automation and natural language to discover and use data like experts, and technical teams can easily build and deploy secure data and AI apps and products. With origins in academia and the open source community, Databricks was founded in 2013 by the original creators of the lakehouse architecture and open source projects Apache Spark™, Delta Lake, MLflow and Unity Catalog.

Please review the specific job listing or contact Databricks's recruiting team for details on remote or hybrid work options for this role.

Salary information may vary by role and location. Please check the specific job listing or discuss compensation during the interview process.

Databricks is an established organization in its industry. The company is a certified Most Loved Workplace®, highlighting a strong, positive culture and committed workforce.

Key benefit categories include: Health & Wellness, Work-Life Balance, Office & Lifestyle, Professional Development, Financial. You can view more details on their CertCheck profile.

The day-to-day environment is guided by core values such as Bias for Action and First Principles Innovation and Collaborative Excellence.

The company has committed to inclusive practices including: Customer Obsession with Integrity and Empowering Every Team Member.

They score particularly well in the area of Systemic Collaboration. They have earned Most Loved Workplace® certifications including: Global Top 100 Most Loved Workplaces® and Certified Most Loved Workplaces® 2025.

Databricks currently has 789 open positions. They are hiring across departments like Field Engineering - Other, Delivery Solutions Architects, Enterprise Sales. You can view all current openings at certcheck.mostlovedworkplace.com/companies/databricks/jobs.

The interview process typically involves an initial recruiter screen followed by team interviews. Please contact Databricks's recruiting team for specific details on this role's process.