Senior Staff Backline Engineer - Data & AI

Cacheflow; San Francisco (CA); On-site; USD 170,000 - 256,000; Full time

Job summary

Cacheflow is seeking an experienced individual with deep expertise in Data Engineering, Product Supportability, or AI to join their Backline Engineering Team. This position involves resolving complex technical issues, optimizing performance, and influencing product enhancements through data insights.

The ideal candidate has at least 10 years of experience, strong programming skills in Python, SQL, or Scala, and a commitment to fostering a diverse and inclusive culture. The role offers a competitive salary and potential bonuses.

Qualifications

• Minimum 10 years of relevant experience.
• Deep expertise in Data Engineering, Product Supportability, or AI Track.
• Strong programming skills in Python, SQL, or Scala.

Responsibilities

• Conduct deep-dive forensics into Spark core internals.
• Perform advanced code-level analysis to identify root causes.
• Optimize architectural performance across the Data and AI stack.
• Analyze global issue trends to influence product roadmap.
• Develop automated workflows and AI-driven diagnostic tools.

Skills

Spark

Data Engineering

Troubleshooting

ETL pipelines

Machine Learning

Python

SQL

Java

Scala

Job description

P-1381

At Databricks, we are passionate about enabling Data & AI teams to solve the world's toughest problems. We do this by building and running the world's best data and AI infrastructure platform so customers can use deep data insights to improve their business.

About the Team

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, delivering exceptional customer satisfaction through deep technical expertise, proactive issue resolution and continuous platform improvements.

What your impact will be

• Deep Dive Troubleshooting: 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.
• Root Cause Analysis: 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.
• Architectural Optimization: Optimize architectural performance across the Data and AI stack by refining execution parameters and enforcing best‑practice strategies to maximize resource efficiency and throughput.
• Product Improvements: Analyze global issue trends and patterns to partner directly with Product Engineering, influencing the product roadmap and driving initiatives that enhance long‑term supportability.
• Scalability & Tooling: Develop reproduction frameworks, automated workflows, and AI‑driven diagnostic tools that translate complex back‑line findings into standardized resolution paths to empower and scale the broader organization.

What we look for

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. Since each track calls for a different set of technical capabilities, we’re looking for excellence in one area rather than proficiency in all.

• Data Engineering Track: 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. Solid programming skills in Python, SQL, or Scala.
• Product Supportability Track: 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.
• AI Track: 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 operationalization.

Pay Range Transparency

Pay range: $170.40—$255.60 USD. The total compensation package for this position may include eligibility for annual performance bonus, equity, and benefits.

Commitment to Diversity and Inclusion

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 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.