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Databricks Jobs in Toronto, ON (NOW HIRING)

Flexstaf IT

Data Science Developer - Senio

Toronto, ON · On-site

MUST HAVES Must Haves: * 5+ years experience Azure environment * 5+ years experience Data engineering with ADF and Databricks * 5+ years experience Programming experience with Python, SQL Location: 3 ...

ShyftLabs

Data Engineer

Toronto, ON · Hybrid

CA$100K - CA$140K/yr

Design, implement, and optimize big data pipelines in Databricks. * Develop scalable ETL workflows to process large datasets. * Leverage Apache Spark for distributed data processing and real-time ...

Bits In Glass

Sr. Data Engineer

Toronto, ON · Remote

Hands-on experience with data lake and warehouse technologies (e.g., Databricks, Snowflake, Redshift, Synapse). * Deep understanding of data modeling, data integration, and ETL/ELT design.

Royal Bank of Canada

Staff Data Engineer

Toronto, ON · On-site

Manage Azure Databricks clusters, compute resources, and workspace optimization for scalable data processing * Optimize Power BI reporting infrastructure, semantic models, and dashboard performance ...

Bits In Glass

Sr. Data Engineer

Toronto, ON · On-site

Hands-on experience with data lake and warehouse technologies (e.g., Databricks, Snowflake, Redshift, Synapse). * Deep understanding of data modeling, data integration, and ETL/ELT design.

Cineplex

Sr. Data Engineer

Toronto, ON · Hybrid

Own and support data integrations between Databricks, Braze, and other customer engagement platforms. * Design reliable and secure pipelines that enable audience activation across marketing ...

Scotiabank

Data Engineer

Toronto, ON · On-site

This role will focus on modern data engineering practices, including Azure, Databricks, Unity Catalog, ETL/ELT pipeline development, dbt-based transformation, CI/CD automation, and data platform ...

DoiT

Senior Technical Content Writer

Toronto, ON · Remote

Research, outline, draft, and revise comprehensive guides on Databricks and Snowflake cost management topics (compute optimization, job cluster configuration, Unity Catalog economics, photon ...

Menlo Ventures

Director, Field Engineering

Toronto, ON · On-site

$250/hr

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 ...

Vangard, Inc.

Sr Data Engineer, Specialist

Toronto, ON · On-site

CA$90K - CA$140K/yr

We are looking for a Sr Data Engineer with in-depth expertise in AWS, Databricks, and modern data architecture and data modeling to help build the next generation of our data foundation , including ...

GEI Consultants

AI Engineer

Markham, ON · On-site

CA$110K - CA$150K/yr

Azure or Databricks certifications (e.g., Azure AI Engineer Associate, Azure Solutions Architect Expert, Databricks ML Professional, Databricks Data Engineer Professional) are a plus. We are GEI.

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Databricks information

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$81.6K

$130.2K

$160.3K

How much do databricks jobs pay per year?

As of Sep 9, 2026, the average yearly pay for databricks in Toronto, ON is $130,225.00, according to ZipRecruiter salary data. Most workers in this role earn between $119,769.00 and $146,491.00 per year, depending on experience, location, and employer.

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.

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 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.

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.

Does Databricks hire remote employees?

Databricks offers remote work opportunities for certain roles, especially those related to software engineering, data science, and cloud infrastructure. The availability of remote positions depends on the specific job and team requirements, and candidates should review individual job postings for location details.

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 involve working with tools like Apache Spark and machine learning. Employee reviews often cite a collaborative environment and opportunities for skill development, though experiences can vary by role and location.

What are jobs in Databricks?

Jobs in Databricks refer to roles that involve developing, managing, and optimizing data workflows using the Databricks platform, which is built on Apache Spark. These positions often require skills in data engineering, data science, or machine learning, and may involve working with cloud environments, SQL, and programming languages like Python or Scala.

What are the most commonly searched types of Databricks jobs in Toronto, ON?

The most popular types of Databricks jobs in Toronto, ON are:

What are popular job titles related to Databricks jobs in Toronto, ON?

For Databricks jobs in Toronto, ON, the most frequently searched job titles are:

What job categories do people searching Databricks jobs in Toronto, ON look for?

The top searched job categories for Databricks jobs in Toronto, ON are:

Databricks jobs near you
Infographic showing various Databricks job openings in Toronto, ON as of September 2026, with employment types broken down into 84% Full Time, 10% Part Time, and 6% Contract. Highlights an 78% Physical, 4% Hybrid, and 18% Remote job distribution, with an average salary of $130,225 per year, or $62.6 per hour.

Data Science Developer - Senio

Toronto, ON • On-site

Flexstaf IT
See more jobs at Flexstaf ITexternal

Full-time

Re-posted yesterday

Job description

MUST HAVES

Must Haves:

  • 5+ years experience Azure environment
  • 5+ years experience Data engineering with ADF and Databricks
  • 5+ years experience Programming experience with Python, SQL

Location: 3 days onsite 

Responsibilities

- Participate in product teams to analyze systems requirements, architect, design, code and implement cloud-based data and analytics products that conform to standards

- Design, create, and maintain cloud-based data lake and lakehouse structures, automated data pipelines, analytics models

- Liaises with cluster IT colleagues to implement products, conduct reviews, resolve operational problems, and support business partners in effective use of cloud-based data and analytics products.

- Analyze complex technical issues, identify alternatives and recommend solutions.

- Support the migration of legacy data pipelines from Azure Synapse Analytics and Azure Data Factory (including stored procedures, views used by BI teams, and Parquet files in Azure Data Lake Storage (ADLS)) to modernized Databricks-based solutions leveraging Delta Lake and native orchestration capabilities

- Support the development of standards and a reusable framework that streamlines pipeline creation

- Participate in code reviews and prepare/conduct knowledge transfer to maintain code quality, promote team knowledge sharing, and enforce development standards across collaborative data projects.

General Skills

- Experience in multiple cloud-based data and analytics platforms and coding/programming/scripting tools to create, maintain, support and operate cloud-based data and analytics products, with a preference for Microsoft Azure

- Experience with designing, creating and maintaining cloud-based data lake and lakehouse structures, automated data pipelines, analytics models in real world implementations

- Strong background in building and orchestrating data pipelines using services like Azure Data Factory and Databricks

- Demonstrated ability to organize and manage data in a lakehouse following medallion architecture;

- Background with Databricks Unity Catalog for governance is a plus

- Proficient in using Python and SQL for data engineering and analytics development

- Familiar with CI/CD practices and tools for automating deployment of data solutions and managing code lifecycle

- Comfortable conducting and participating in peer code reviews in GitHub to ensure quality, consistency, and best practices

- Experience in assessing client information technology needs and objectives

- Experience in problem-solving to resolve complex, multi-component failures

- Experience in preparing knowledge transfer documentation and conducting knowledge transfer

- Experience working on an Agile team

Desirable Skills

- Written and oral communication skills to participate in team meetings, write/edit systems documentation, prepare and present written reports on findings/alternate solutions, develop guidelines / best practices

- Interpersonal skills to explain and discuss advantages and disadvantages of various approaches

Technology Stack

- Azure Storage, Azure Data Lake, Azure Databricks Lakehouse, Azure Synapse, Azure Databricks

- Python, SQL

- Power BI

- GitHub