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Intern Databricks Data Engineer Jobs in Toronto, ON

Remote Full-time Senior Data Engineer Are you an experienced Data Engineering professional with a ... Databricks: Delta Lake, Unity Catalog, Delta Live Tables (DLT), and Spark optimization. GCP:

We are seeking a hands-on Data Engineer to support the Total Fund Management Portfolio Management ... with Databricks * • Prior consulting, advisory, or client-facing delivery experience * • ...

25-167 Data Engineer

Oshawa, ON · Hybrid

$75 - $95/hr

We are looking for strong hands on Data Engineering skillset focused heavily on Azure Data Factory and Databricks (use of PySpark and SparkSQL). Build and productionize modular and scalable data ELT ...

You will work primarily on Spark based data processing running on Azure Databricks, developing ... This is an engineering heavy role for someone who enjoys writing clean, efficient code and ...

Senior Data Engineer Resume Due Date: Wednesday, June 25, 2025 (5:00PM EST) Number of Vacancies: 2 ... Databricks, Collibra, and Power Bl. Work within the agile SCRUM work management framework in ...

AI Engineer

Concord, ON

CA$110K - CA$150K/yr

The AI Engineer is responsible for the development of AI solutions, typically leveraging pretrained ... Knowledge of big data technologies such as Spark and Databricks; familiarity with TensorFlow and ...

Data Engineer

Toronto, ON · Hybrid

CA$86K - CA$136K/yr

Demonstrable experience with Databricks, including building and maintaining data pipelines ... Strong programming skills in languages such as Python, SQL, or Scala. * Excellent problem-solving ...

AI Engineer

Markham, ON

CA$110K - CA$150K/yr

The AI Engineer is responsible for the development of AI solutions, typically leveraging pretrained ... Knowledge of big data technologies such as Spark and Databricks; familiarity with TensorFlow and ...

Lead, Data Engineer

Mississauga, ON · On-site +1

CA$122K - CA$162K/yr

Summary The Lead Data Engineer is a senior individual contributor within McKesson's Decision ... Databricks, Snowflake, Azure Data Factory * Confluent Kafka / Azure Event Hub * PySpark and ...

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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.

What are the most commonly searched types of Databricks Data Engineer jobs in Toronto, ON? The most popular types of Databricks Data Engineer jobs in Toronto, ON are:
What job categories do people searching Intern Databricks Data Engineer jobs in Toronto, ON look for? The top searched job categories for Intern Databricks Data Engineer jobs in Toronto, ON are:
Senior Data Engineer

Senior Data Engineer

Fusemachines

Toronto, ON • Remote

Contractor

Posted 26 days ago


Job description

About Fusemachines

Founded in 2013, Fusemachines is a global provider of enterprise AI products and services, on a mission to democratize AI. Leveraging proprietary AI Studio and AI Engines, the company helps drive the clients’ AI Enterprise Transformation, regardless of where they are in their Digital AI journeys. With offices in North America, Asia, and Latin America, Fusemachines provides a suite of enterprise AI offerings and specialty services that allow organizations of any size to implement and scale AI. Fusemachines serves companies in industries such as retail,  manufacturing, and government.
Fusemachines continues to actively pursue the mission of democratizing AI for the masses by providing high-quality AI education in underserved communities and helping organizations achieve their full potential with AI.
Type: Remote Full-time

Senior Data Engineer

Are you an experienced Data Engineering professional with a passion for building scalable, reliable, and high-performance data systems? Do you have hands-on experience designing and optimizing end-to-end real-time and batch pipelines, and developing cloud-native data architectures using modern technologies such as AWS, GCP, Azure, Databricks, and Snowflake?


We are looking for a Senior Data Engineer to architect, design, and implement scalable, high-performance data solutions. The ideal candidate will be an expert in at least one major cloud data ecosystem (AWS, Azure, GCP, Snowflake, or Databricks) and possess a deep understanding of the end-to-end data lifecycle, from ingestion to business intelligence.
Qualification & Skill Set Requirements
Core Technical Competencies
Experience: 5+ years of hands-on data engineering experience in a production environment.
Languages: Strong proficiency in Python, SQL (complex queries, performance tuning), and PySpark/Apache Spark.
Data Modeling: Expert knowledge of data modeling (3NF, Star, Snowflake Schema) and Lakehouse/Warehouse architectures.
ETL/ELT & Orchestration: Proven experience building pipelines using tools like dbt, Airflow, Dagster, or native cloud orchestrators (Glue, Data Factory, Composer).
Integrations: Experienced in integrating data from diverse sources: APIs, RDBMS/NoSQL databases, flat files, and streaming platforms (Kafka, Kinesis, Pub/Sub).
Cloud Platform Expertise (Specialization-Specific)
Candidates should demonstrate deep expertise in anyone of the following:
Snowflake: SnowSQL, Streams, Tasks, Snowpark, and cost optimization.
Databricks: Delta Lake, Unity Catalog, Delta Live Tables (DLT), and Spark optimization.
GCP: BigQuery, Dataflow, Dataproc, Pub/Sub, and Cloud Functions.
Azure: Synapse Analytics, Data Factory, Azure Databricks, and Stream Analytics.
AWS: Redshift, S3, Lake Formation, Glue, and Lambda.
Professional Practices
SDLC & DevOps: Proficient in Git workflows, CI/CD pipelines (GitHub Actions, Azure DevOps, AWS CodePipeline), and IaC (Terraform/CloudFormation).
Data Governance: Strong understanding of data quality, lineage, observability, security (RBAC, encryption), and compliance frameworks.
Agile: Active experience in Agile/Scrum environments using Jira or Azure Boards.
Mentorship: Ability to lead projects and provide technical guidance to junior/mid-level engineers.
Responsibilities
Architecture: Architect, design, and implement scalable, reliable data solutions and pipelines aligned with business analytics needs.
Optimization: Manage and fine-tune cloud resources and workloads for maximum performance, reliability, and cost-efficiency.
Data Transformation: Lead the development of ETL/ELT processes for both batch and real-time data processing.
Collaboration: Partner with Product, Engineering, and Data Science teams to deliver effective, data-driven solutions.
Governance & Quality: Promote and enforce best practices in data governance, security, and data quality frameworks.
Mentorship: Provide technical leadership and mentorship to the team, ensuring architecture quality and best practices.
Documentation: Maintain comprehensive documentation of data architectures, configurations, and workflows.
Fusemachines is an Equal Opportunities Employer, committed to diversity and inclusion. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or any other characteristic protected by applicable federal, state, or local laws.

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