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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 Jun 13, 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.

What is a Databricks job?

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 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 are popular job titles related to Databricks jobs in Ontario? For Databricks jobs in Ontario, the most frequently searched job titles 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

Data Engineer - Spark, Databricks & Snowflake (Energy)- DESDSAS

NavitasPartners

Ottawa, ON • On-site

CA$30/hr

Full-time

Posted 8 days ago

Job description

Job Title : Data Engineer – Spark, Databricks & Snowflake (Energy)Industry

Energy & Utilities

Position Overview

We are seeking an experienced Data Engineer to design, build, and optimize large-scale data platforms supporting operational, customer, asset, and energy market analytics. The ideal candidate will have strong expertise in Databricks, Spark, Snowflake, and cloud-based data engineering solutions.

Responsibilities
  • Develop scalable ETL/ELT pipelines using Spark and Databricks.
  • Build enterprise data solutions on Snowflake.
  • Integrate data from SCADA, IoT sensors, smart meters, ERP, CRM, and trading systems.
  • Design batch and real-time data ingestion frameworks.
  • Optimize data performance, reliability, and scalability.
  • Implement data quality and monitoring processes.
  • Support predictive maintenance and asset performance analytics initiatives.
Required Skills
  • Apache Spark (PySpark, Spark SQL)
  • Databricks
  • Snowflake
  • Python, SQL
  • Azure Data Factory, AWS Glue, or GCP Dataflow
  • Kafka/Event Streaming
  • Delta Lake
  • CI/CD and DevOps practices
Preferred Skills
  • Smart Grid Analytics
  • Energy Trading Data
  • Renewable Energy Operations
  • IoT and Time-Series Data Management
Mandatory Experience
  • 5+ years of Data Engineering experience.
  • Must have prior experience working within the Energy, Utilities, Oil & Gas, Renewable Energy, or Energy Trading sector.

For more details reach at resumes@navitassols.com