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Added 10 days ago
Regulatory/Financial Reporting Developer (Databricks, Snowflake, Axiom)
Axelon Services Corporation
Montreal, QC
$77.93 USD / hour
Other
Minimum 3 years of software development experience in Scala/Spark (Java).
Added 10 days ago
Senior Java Developer, TD Securities
TD
Toronto, ON
Full-time
We are looking for a motivated Senior Java Developer (Engineer I) to join our Trading Risk Warehouse platform team within TD Securities. The successful candidate will contribute to the…
Added 9 days ago
SimCorp Dimension (SCD) Specialist
Munich Re
Toronto, ON
Added 10 days ago
Senior Software Developer (Data & Backend Development)
Autodesk
Toronto, ON · Montreal, QC · AMER - Canada - Ontario - Toronto - University Ave
Full-time
Proficiency in programming languages (we use Python, Java/Scala)
Added 9 days ago
Data Engineer
Synpulse
Toronto, ON
Proficiency in SQL and Python; knowledge of Spark, PySpark, Scala, or Java is a strong asset.
Added 10 days ago
Big Data Developer
Cognizant
Toronto, ON
$53,000 to $108,000 CAD / year
Full-time
Experience developing applications and APIs using Scala or Java.
Added 4 months ago
Field Engineering Co-Op
Acceldata
Kitchener, Ontario
Internship
Collaborate with the field engineering team to write, test, and deploy software solutions using advanced Java or Scala programming.
Added 4 months ago
Software Engineering Co-op
Acceldata
Kitchener, Ontario
Internship
Collaborate with the engineering team to write, test, and deploy software solutions using advanced Java or Scala programming.
Added 10 days ago
Financial Reporting Developer
LanceSoft, Inc.
Montreal, QC
Contract
3+ years software development experience in Scala/Spark (Java)
Added 13 days ago
Director & Principal Engineer, AI/ML & MLOps Platform
Royal Bank of Canada
Vancouver, BC
Full-time
Deep expertise in modern distributed data processing and ML engineering tools and languages (e.g., Python, Java/Scala, PySpark/Spark, Kafka, SQL, orchestration frameworks).
Added 11 days ago
Lead, Data Engineering
RBC
Toronto, ON
Full-time
Proficiency in writing and optimizing SQL queries and at least one programming languages like Java, Scala or Python
Added 11 days ago
Lead, Data Engineering
Royal Bank of Canada
Toronto, ON
Full-time
Proficiency in writing and optimizing SQL queries and at least one programming languages like Java, Scala or Python
Added 11 days ago
Sr. Lead Engineer, TD Securities
TD
Toronto, ON
Full-time
Strong experience with Hadoop, Spark, Parquet or similar Big Data technologies.
Added 12 days ago
Senior Data Engineer (Hadoop Migration)
Capgemini
Toronto, ON
Programming experience in at least two of the following languages: Scala, Java or Python
Added 2 months ago
Senior Back End Engineer (Data Platform)
Forma.ai
Toronto, Ontario
Proficiency in at least one production-grade language such as Python, Java, Scala, Kotlin, Go, C#, or similar.
Added 3 months ago
Full-Stack Software Developer
Engineered Intelligence Inc.
Mississauga, Ontario
Full-time
The Position: Do our values align with you? Are you an experienced Full-Stack Software Developer looking to join a dedicated team working together to build rewarding careers and an…
Added 3 months ago
Engineering Manager, Data AI & Analytics
''
Toronto, Ontario
Full-time · Other
Proficiency in one or more languages such as Python, SQL, Java, Scala, Spark, or PySpark
Added 4 months ago
Field Engineering Co-Op
Acceldata
Kitchener, Ontario
Internship
Collaborate with the field engineering team to write, test, and deploy software solutions using advanced Java or Scala programming.
Added 1 month ago
Senior Staff Backline Engineer - Data & AI
Databricks
Vancouver, BC
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…
Added 1 month ago
Staff Software Engineer - Backend
Databricks
Vancouver, BC
10+ years of production level experience in either Java, Scala or C++.
Added 1 month ago
Senior Software Engineer - Backend
Databricks
Vancouver, BC
5+ years of production level experience in either Java, Scala or C++.

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Databricks

Senior Staff Backline Engineer - Data & AI

Vancouver, BC, Canada

Pay: $170.40 - $255.60 USD
Posting language: English
Posted: Aug 11, 2026

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Original job description

P-1381

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. And we're only getting started.

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 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.

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 backline findings into standardised resolution paths to empower and scale the broader organisation.

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. 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.
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

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. 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 here.

Local Pay Range

$170.40 - $255.60 USD

About Databricks

Databricks is the Data and AI company. More than 20,000 organizations worldwide - including adidas, AT&T, Bayer, Block, Mastercard, Rivian, Unilever, and 70% of the Fortune 500 - rely on the Databricks Data + AI Platform to build and scale data and AI apps, analytics and agents. Headquartered in San Francisco with 30+ offices around the globe, Databricks offers a unified platform that includes Genie, Lakebase, Agent Bricks, Lakeflow, Lakehouse, and Unity Catalog. To learn more, follow Databricks on LinkedIn, X, YouTube, and Instagram.

Benefits

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 here.

Our 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 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.

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More about this job

Responsibilities

The role involves deep-dive forensics into Spark core internals and the broader Data & AI ecosystem to resolve high-priority architectural failures and complex system anomalies through advanced code-level analysis. Responsibilities also include optimizing architectural performance, partnering with Engineering on product improvements based on global issue trends, and developing automated tooling to scale resolution paths.

Requirements

Candidates must have 10+ years of relevant experience and deep expertise in one of three tracks: Data Engineering (Spark/Delta Lake/ETL), Product Supportability (distributed systems internals/code-level analysis), or AI (large-scale ML/Generative AI systems). Proven experience managing both customers and technical stakeholders is required.

Skills

Spark
Delta Lake
Hive
Python
SQL
Scala
Java
Distributed System Internals
Code-Level Root-Cause Analysis
Profiling
Machine Learning
Generative AI
LLM-Based Applications
ML Lifecycle Management
Troubleshooting
Performance Optimization

Visa sponsorship

Not detected in the job text

Keywords

Data
AI
Backline Engineering
Support
Escalations
Customer Success
Automation
Tooling
Spark
Delta Lake
Hive
ETL Pipelines
Python
SQL
Scala
Java
Distributed Systems
Profiling
Machine Learning
Generative AI
LLM
MLOps
Performance Tuning
Root Cause Analysis
Architecture Optimization
Data Intelligence Platform

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