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Databricks Data Engineer information

See Ontario salary details

$25.5K

$119.5K

$185K

How much do databricks data engineer jobs pay per year?

As of Jun 9, 2026, the average yearly pay for databricks data engineer in Ontario is $119,535.00, according to ZipRecruiter salary data. Most workers in this role earn between $93,500.00 and $148,000.00 per year, depending on experience, location, and employer.

What is a Databricks Data Engineer job?

A Databricks Data Engineer is responsible for designing, building, and maintaining scalable data pipelines on the Databricks platform. They work with Apache Spark, Delta Lake, and cloud services to process large datasets efficiently. Their role involves data ingestion, transformation, optimization, and ensuring data quality for analytics and machine learning. Additionally, they collaborate with data scientists, analysts, and business teams to deliver reliable data solutions.

What does a typical day look like for a Databricks Data Engineer?

A typical day for a Databricks Data Engineer involves developing and maintaining scalable data pipelines, optimizing big data workflows using Spark, and collaborating with data scientists, analysts, and other engineers. You will regularly work within cloud environments to manage and process large datasets, conduct troubleshooting, and ensure data reliability and performance. Daily tasks may also include writing code, participating in team meetings, and implementing best practices for data security and governance. This role is highly collaborative, requiring frequent communication to align on project goals and address any technical challenges. The dynamic, project-based structure helps expand your skills and offers growth opportunities into senior engineering or data architecture roles.

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

To thrive as a Databricks Data Engineer, you need strong expertise in data engineering concepts, big data processing, and programming languages such as Python, Scala, or SQL, often supported by a degree in computer science or a related field. Proficiency in Databricks, Apache Spark, cloud platforms (like AWS, Azure, or GCP), and relevant certifications such as Databricks Certified Data Engineer are highly valued. Effective problem-solving, collaboration, and clear communication skills help engineers work efficiently within cross-functional teams. These skills are essential for designing scalable data pipelines, ensuring data quality, and delivering actionable analytics in dynamic business environments.

What are the most commonly searched types of Databricks Data Engineer jobs in Ontario? The most popular types of Databricks Data Engineer jobs in Ontario are:
What are popular job titles related to Databricks Data Engineer jobs in Ontario? For Databricks Data Engineer jobs in Ontario, the most frequently searched job titles are:
What job categories do people searching Databricks Data Engineer jobs in Ontario look for? The top searched job categories for Databricks Data Engineer jobs in Ontario are:
Databricks Data Engineer jobs near you
Infographic showing various Databricks Data Engineer job openings in Ontario as of June 2026, with employment types broken down into 1% As Needed, 94% Full Time, 3% Part Time, 1% Temporary, and 1% Contract. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution, with an average salary of $119,535 per year, or $57.5 per hour.

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

NavitasPartners

Hamilton, ON • On-site

$30/hr

Other

Posted 6 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

Apply