Senior Staff Backline Engineer - Data & AI

Databricks; Dallas/Red Rose; On-site; CAD 319,595 - 479,393; Full time

Benefits offered by this job

Comprehensive benefits package

Annual performance bonus

Equity options

Job summary

Databricks is looking for a senior technical expert to join the Backline Engineering Team in Manitoba. With a focus on data engineering, you will conduct deep troubleshooting, perform root cause analysis, and optimize system performance across the Data and AI ecosystem. Candidates should have 10+ years of experience, deep expertise in data engineering or AI, and strong programming skills. The position offers a competitive pay range of $170.40 to $255.60 USD, along with comprehensive benefits.

Qualifications

• 10+ years of relevant experience with proven customer management.
• Expertise in analyzing and optimizing performance issues in distributed systems.
• Strong programming skills in Python, SQL, or Scala.

Responsibilities

• Conduct deep-dive troubleshooting for high-priority architectural failures.
• Perform root cause analysis and resource profiling.
• Optimize architectural performance across the Data and AI stack.
• Drive product improvements by analyzing global issue trends.
• Develop automated workflows and AI-driven diagnostic tools.

Skills

Deep expertise in data engineering

Proficiency in Python, SQL, or Scala

Experience with Spark, Delta Lake, or Hive

Ability to perform root-cause analysis

Knowledge of large-scale machine learning systems

Job description

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. With a strong focus on customer success, we deliver exceptional customer satisfaction by providing 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: Optimise architectural performance across the Data and AI stack by refining execution parameters and enforcing best practice strategies to maximise resource efficiency and throughput.
• Product Improvements: Analyse 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 standardised resolution paths to empower and scale the broader organisation.

What We Look For

Customer‑obsessed candidates with 10+ years of relevant experience, including deep expertise in one of the following tracks, and proven experience in managing customers and technical stakeholders. We seek 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. Demonstrated problem‑solving ability and understanding of data engineering best practices. Solid hands‑on 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 operationalisation. Skilled in diagnosing and optimising distributed ML workloads for performance and scalability.

Pay Range Transparency

Local Pay Range: $170.40—$255.60 USD. The total compensation may also include eligibility for annual performance bonus, equity, and benefits.

Benefits

At Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all our employees.

Our Commitment to Diversity and Inclusion

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.

Compliance

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.