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Intern Databricks Data Engineer information

What is the difference between Intern Databricks Data Engineer vs Intern Data Analyst?

AspectIntern Databricks Data EngineerIntern Data Analyst
Required SkillsSQL, Python, Spark, Databricks platformExcel, SQL, data visualization tools
Work EnvironmentData engineering teams, cloud platformsBusiness intelligence teams, reporting environments
Industry UsageTech, finance, healthcareRetail, marketing, finance

Intern Databricks Data Engineers focus on building data pipelines and managing large-scale data workflows using Databricks and Spark, while Intern Data Analysts primarily analyze data and create reports. Both roles require SQL and basic programming skills, but Data Engineers need more technical expertise in data infrastructure, whereas Data Analysts focus on interpreting data for business insights.

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Intern Databricks Data Engineer jobs near you
Infographic showing various Intern Databricks Data Engineer job openings in Ontario as of June 2026, with employment types broken down into 87% Full Time, and 13% Part Time. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution.

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

NavitasPartners

Kingston, ON

CA$30/hr

Full-time

Posted 7 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