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Databricks Jobs in Ontario (NOW HIRING)

Databricks

Lakebase Sales Specialist

Toronto, ON

Databricks is seeking a Lakebase Sales Specialist to help customers modernize their operational data foundation with Databricks Lakebase , our fully-managed Postgres offering for intelligent ...

Databricks

Director, Field Engineering

Toronto, ON

To embody and promote Databricks' customer-obsessed, teamwork and diverse culture * Support increased return on investment of Solutions Architect involvement in sales cycles * Create trust-based ...

United Airlines

Data Engineer (Databricks)

Mississauga, ON

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Design, build, and optimise scalable data pipelines and ETL/ELT workflows using Databricks (Unity Catalog, Delta Live Tables, Workflows, Asset Bundles), Apache Spark, and Scala to process large ...

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Databricks information

See Ontario salary details

$85.5K

$136.5K

$168K

How much do databricks jobs pay per year?

As of Aug 17, 2026, the average yearly pay for databricks in Ontario is $136,456.00, according to ZipRecruiter salary data. Most workers in this role earn between $125,500.00 and $153,500.00 per year, depending on experience, location, and employer.

Are Databricks in high demand?

Databricks-related roles, such as data engineers and data scientists, are in high demand due to the platform's widespread adoption for big data analytics and machine learning. Skills in Spark, cloud environments, and data pipeline development increase employability in this field.

What are jobs in Databricks?

Jobs in Databricks refer to employment positions that involve working with the Databricks platform, which is used for big data analytics and machine learning. These roles often require skills in data engineering, data science, or software development, and may involve working with tools like Apache Spark and cloud environments. Job responsibilities can include developing data pipelines, analyzing large datasets, and optimizing performance within the Databricks environment.

What is a Databricks?

A Databricks job is a way to run an automated workload, such as a data pipeline, machine learning model training, or ETL task, on the Databricks platform. Jobs can be scheduled, triggered manually, or run as part of a workflow. They support different task types, including notebooks, Python scripts, JARs, and SQL queries. Databricks jobs also allow for dependency management and orchestration across multiple tasks within a workflow.

Is Databricks a good company to work for?

As a company, Databricks is known for its focus on data analytics and cloud-based platforms, offering roles that often require skills in Spark, Python, and cloud services. Employee reviews highlight a collaborative environment and opportunities for growth, but experiences can vary depending on the role and team. Job seekers should consider researching specific positions and company culture to determine fit.

What are the key skills and qualifications needed to thrive in the Databricks position, and why are they important?

To thrive in a Databricks role, you need strong programming skills in languages such as Python or Scala, a deep understanding of data engineering or data science principles, and typically a relevant degree in computer science or a related field. Experience with Apache Spark, cloud platforms like Azure or AWS, and Databricks-specific certifications are often highly valued. Exceptional problem-solving, communication, and collaboration skills help professionals excel within multidisciplinary data teams. These capabilities are crucial for successfully designing, developing, and optimizing large-scale data solutions in a fast-evolving analytics environment.

What are the typical daily responsibilities of someone working in a Databricks role?

Professionals in Databricks roles typically spend their days developing and maintaining data pipelines, analyzing large datasets, and collaborating with business stakeholders to translate requirements into scalable solutions. They often use tools such as Apache Spark and cloud platforms to design and optimize workflows, while troubleshooting data quality or performance issues that arise. Regular teamwork with data engineers, analysts, and software developers is common, as is participating in sprint planning or code review sessions. Overall, the role combines hands-on technical work with ongoing collaboration to ensure data-driven insights and infrastructure reliability.

What are the most commonly searched types of Databricks jobs in Ontario?

The most popular types of Databricks jobs in Ontario are:

What job categories do people searching Databricks jobs in Ontario look for?

The top searched job categories for Databricks jobs in Ontario are:

What cities in Ontario are hiring for Databricks jobs?

Cities in Ontario with the most Databricks job openings:

Databricks jobs near you
Infographic showing various Databricks job openings in Ontario as of August 2026, with employment types broken down into 92% Full Time, 1% Part Time, and 7% Contract. Highlights an 79% Physical, 5% Hybrid, and 16% Remote job distribution, with an average salary of $136,456 per year, or $65.6 per hour.

Business Analyst (DataBricks/DataLake)

Jay Analytix

Toronto, ON • On-site

Full-time

Re-posted 4 days ago

Job description

Business Analyst Databricks & Data Lake

Location: Toronto, ON (Hybrid 3 days onsite per week) Experience: Minimum 8+ years Employment Type: Full-Time / Contract (as applicable)

About the Role

We are seeking an experienced Business Analyst with strong hands-on exposure to Databricks and modern Data Lake / Lakehouse platforms to join our Toronto-based team. In this role, you will act as the bridge between business stakeholders and data engineering teams gathering requirements, defining data mappings and transformation logic, and driving the delivery of large-scale data platform and migration initiatives. The ideal candidate combines deep business analysis fundamentals with practical knowledge of cloud data ecosystems.

Key Responsibilities
  • Elicit, document, and manage business and data requirements for data lake, lakehouse, and analytics initiatives, translating them into functional and technical specifications
  • Work closely with data engineers, architects, and platform teams to define source-to-target mappings, data transformation rules, and data quality requirements
  • Support the design and delivery of solutions on Databricks (Delta Lake, notebooks, workflows, Unity Catalog) and cloud data lake platforms (Azure Data Lake Storage, AWS S3, or GCP)
  • Analyze and profile source system data to assess quality, completeness, and fitness for migration or integration
  • Define and document data lineage, business glossaries, and metadata to support data governance initiatives
  • Develop and execute test plans, including UAT coordination, data validation, and reconciliation between legacy and target platforms
  • Create process flows, user stories, use cases, and acceptance criteria within Agile delivery frameworks
  • Facilitate workshops and requirement sessions with business users, product owners, and technical teams
  • Support prioritization and backlog management with product owners; track requirements through to delivery
  • Produce clear documentation and communicate findings, risks, and recommendations to both technical and non-technical stakeholders
Required Qualifications
  • 8+ years of experience as a Business Analyst, with significant time spent on data-focused projects (data platforms, data warehousing, migrations, analytics)
  • Hands-on experience with Databricks working with notebooks, Delta Lake tables, and understanding of Lakehouse architecture concepts
  • Strong understanding of Data Lake concepts and cloud data platforms (Azure preferred; AWS or GCP also considered) data ingestion, storage layers (raw/curated/consumption), and data pipelines
  • Proficiency in SQL for data profiling, analysis, and validation; ability to read/interpret PySpark or Python code an asset
  • Experience creating source-to-target mapping documents, data dictionaries, and transformation specifications
  • Solid grasp of data governance, data quality, and metadata management practices
  • Experience with Agile methodologies and tools (Jira, Confluence, Azure DevOps)
  • Strong analytical, problem-solving, and critical-thinking skills with high attention to detail
  • Excellent communication, facilitation, and stakeholder management skills across business and technical audiences
  • Bachelor's degree in Business, Computer Science, Information Systems, or a related field
Nice to Have
  • Experience in financial services, banking, or insurance data environments
  • Familiarity with data modeling concepts (dimensional modeling, medallion architecture)
  • Exposure to BI and analytics tools (Power BI, Tableau) and how they consume lakehouse data
  • Knowledge of ETL/ELT tools (Azure Data Factory, Informatica, dbt)
  • Understanding of data privacy and regulatory requirements (PIPEDA, GDPR) as they relate to enterprise data
  • Certifications such as CBAP, PMI-PBA, Azure Data Fundamentals (DP-900), or Databricks Lakehouse Fundamentals
Why Join Us
  • Contribute to high-visibility data modernization initiatives on a leading Lakehouse platform
  • Hybrid work model based in downtown Toronto
  • Collaborative environment working alongside data engineering, governance, and business teams
  • Competitive compensation and benefits package